Compare commits

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21 Commits

Author SHA1 Message Date
jango-blockchained
53a041921b docs: enhance documentation with comprehensive API, architecture, and installation guides
- Add detailed API documentation for core functions, SSE, and WebSocket APIs
- Create comprehensive architecture overview with system design diagrams
- Develop in-depth installation and quick start guides
- Improve troubleshooting documentation with advanced debugging techniques
- Update site navigation and markdown configuration
2025-02-05 02:44:30 +01:00
jango-blockchained
af3399515a docs: enhance documentation site with improved design and features
- Update MkDocs configuration with advanced theme settings
- Add custom color palette and navigation features
- Expand markdown extensions for better documentation rendering
- Include new documentation sections and plugins
- Add custom CSS for improved site styling
- Update site description and navigation structure
2025-02-05 02:33:05 +01:00
jango-blockchained
01991c0060 chore: update documentation site configuration
- Update MkDocs site URL and repository links
- Modify README diagram formatting for improved readability
2025-02-05 02:23:36 +01:00
jango-blockchained
3f8d67b145 chore: refine configuration and setup scripts for improved usability
- Update README with minor text formatting
- Improve Smithery configuration command formatting
- Enhance macOS setup script with WebSocket URL conversion and security hardening
2025-02-05 02:20:08 +01:00
jango-blockchained
ab8b597843 docs: add MCP client integration documentation and scripts
- Update README with integration instructions for Cursor, Claude Desktop, and Cline
- Add configuration examples for different MCP client integrations
- Create Windows CMD script for starting MCP server
- Include configuration files for Claude Desktop and Cline clients
2025-02-05 00:48:45 +01:00
jango-blockchained
ddf9070a64 Merge commit 'f5c01ad83a43dd6495b7906bee63a0652c9d1100' 2025-02-04 22:51:11 +01:00
jango-blockchained
b9727981cc feat(speech): enhance speech processing with advanced audio setup and detection
- Add audio setup script for PulseAudio configuration
- Improve wake word detection with advanced noise filtering
- Implement continuous transcription and command processing
- Update speech Dockerfile with additional audio dependencies
- Enhance logging and error handling in wake word detector
2025-02-04 22:51:06 +01:00
jango-blockchained
e1db799b1d chore(dependencies): update Bun lockfile and package configuration
- Update bun.lock with latest package versions
- Modify Dockerfile to improve dependency installation
- Remove preinstall script from package.json
- Add winston logging dependencies
- Adjust Docker build process for cleaner dependency management
2025-02-04 21:42:50 +01:00
smithery-ai[bot]
f5c01ad83a Update README 2025-02-04 20:29:52 +00:00
smithery-ai[bot]
190915214d Add Smithery configuration 2025-02-04 20:29:51 +00:00
jango-blockchained
905339fb67 refactor(docker): switch to Node.js base image and optimize Bun installation
- Replace Bun base image with Node.js slim image
- Install Bun globally using npm in both builder and runner stages
- Simplify Docker build process and dependency management
- Remove unnecessary environment variables and build flags
- Update docker-build.sh to use BuildKit and remove lockfile before build
2025-02-04 20:18:46 +01:00
jango-blockchained
849b080aba chore: update project dependencies and build configuration
- Remove bun.lockb from version control
- Add comprehensive docker-build.sh script for optimized Docker builds
- Update Dockerfile with multi-stage build and improved resource management
- Add winston logging dependencies to package.json
- Enhance Docker image build process with resource constraints and caching
2025-02-04 20:14:13 +01:00
jango-blockchained
f8bbe4af6f refactor(docker): optimize Dockerfiles for multi-stage builds and production deployment
- Implement multi-stage builds for main and speech Dockerfiles
- Reduce image size by using slim base images
- Improve dependency installation with frozen lockfile and production flags
- Add resource constraints and healthcheck to speech service Dockerfile
- Enhance build caching and separation of build/runtime dependencies
2025-02-04 19:41:23 +01:00
jango-blockchained
3a6f79c9a8 feat(speech): enhance speech configuration and example integration
- Add comprehensive speech configuration in .env.example and app config
- Update Docker speech Dockerfile for more flexible model handling
- Create detailed README for speech-to-text examples
- Implement example script demonstrating speech features
- Improve speech service initialization and configuration management
2025-02-04 19:35:50 +01:00
jango-blockchained
60f18f8e71 feat(speech): add speech-to-text and wake word detection modules
- Implement SpeechToText class with Docker-based transcription capabilities
- Add wake word detection using OpenWakeWord and fast-whisper models
- Create Dockerfile for speech processing container
- Develop comprehensive test suite for speech recognition functionality
- Include audio processing and event-driven transcription features
2025-02-04 19:08:01 +01:00
jango-blockchained
47f11b3d95 docs: update README.md 2025-02-04 18:35:17 +01:00
jango-blockchained
f24be8ff53 docs: remove outdated support and rate limiting sections from README 2025-02-04 18:31:39 +01:00
jango-blockchained
dfff432321 docs: update Jekyll configuration for GitHub Pages and dependencies
- Add repository settings and GitHub metadata plugin
- Update baseurl to match repository name
- Include additional Jekyll and Ruby dependencies in Gemfile
- Simplify configuration by removing redundant sections
2025-02-04 18:00:59 +01:00
jango-blockchained
d59bf02d08 docs: enhance Jekyll configuration with comprehensive site settings
- Add base URL and site configuration for GitHub Pages
- Include remote theme and additional Jekyll plugins
- Configure navigation structure and page layouts
- Set up collections for tools and development sections
- Optimize Gemfile with additional dependencies
2025-02-04 17:58:10 +01:00
jango-blockchained
345a5888d9 docs: update Jekyll configuration for enhanced documentation structure
- Add new documentation pages to header navigation
- Configure collections for tools and development sections
- Set default layouts for pages, tools, and development collections
- Improve documentation site organization and navigation
2025-02-04 17:51:04 +01:00
jango-blockchained
d6a5771e01 docs: enhance project documentation with comprehensive updates
- Revamp README.md with improved project overview, architecture diagram, and badges
- Create new development and tools documentation with detailed guides
- Update API documentation with enhanced examples, rate limiting, and security information
- Refactor and consolidate documentation files for better navigation and clarity
- Add emojis and visual improvements to make documentation more engaging
2025-02-04 17:49:58 +01:00
45 changed files with 4722 additions and 731 deletions

View File

@@ -73,7 +73,6 @@ temp/
.cloud/
*.db
*.db-*
bun.lockb
.cursor/
.cursor*
.cursorconfig

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@@ -102,3 +102,10 @@ TEST_HASS_HOST=http://localhost:8123
TEST_HASS_TOKEN=test_token
TEST_HASS_SOCKET_URL=ws://localhost:8123/api/websocket
TEST_PORT=3001
# Speech Features Configuration
ENABLE_SPEECH_FEATURES=false
ENABLE_WAKE_WORD=true
ENABLE_SPEECH_TO_TEXT=true
WHISPER_MODEL_PATH=/models
WHISPER_MODEL_TYPE=base

View File

@@ -1,23 +1,70 @@
# Use Bun as the base image
FROM oven/bun:1.0.25
# Use Node.js as base for building
FROM node:20-slim as builder
# Set working directory
WORKDIR /app
# Copy package files
# Install bun
RUN npm install -g bun@1.0.25
# Install only the minimal dependencies needed and clean up in the same layer
RUN apt-get update && apt-get install -y --no-install-recommends \
ca-certificates \
curl \
&& rm -rf /var/lib/apt/lists/* \
&& apt-get clean \
&& rm -rf /var/cache/apt/*
# Set build-time environment variables
ENV NODE_ENV=production \
NODE_OPTIONS="--max-old-space-size=2048" \
BUN_INSTALL_CACHE=0
# Copy only package files first
COPY package.json ./
# Install dependencies
RUN bun install
# Install dependencies with a clean slate
RUN rm -rf node_modules .bun bun.lockb && \
bun install --no-save
# Copy source code
COPY . .
# Copy source files and build
COPY src ./src
COPY tsconfig*.json ./
RUN bun build ./src/index.ts --target=bun --minify --outdir=./dist
# Build TypeScript
RUN bun run build
# Create a smaller production image
FROM node:20-slim as runner
# Install bun in production image
RUN npm install -g bun@1.0.25
# Set production environment variables
ENV NODE_ENV=production \
NODE_OPTIONS="--max-old-space-size=1024"
# Create a non-root user
RUN addgroup --system --gid 1001 nodejs && \
adduser --system --uid 1001 bunjs
WORKDIR /app
# Copy only the necessary files from builder
COPY --from=builder --chown=bunjs:nodejs /app/dist ./dist
COPY --from=builder --chown=bunjs:nodejs /app/node_modules ./node_modules
COPY --chown=bunjs:nodejs package.json ./
# Create logs directory with proper permissions
RUN mkdir -p /app/logs && chown -R bunjs:nodejs /app/logs
# Switch to non-root user
USER bunjs
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD curl -f http://localhost:4000/health || exit 1
# Expose port
EXPOSE 4000
# Start the application
CMD ["bun", "run", "start"]
# Start the application with optimized flags
CMD ["bun", "--smol", "run", "start"]

469
README.md
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@@ -1,231 +1,372 @@
# Model Context Protocol (MCP) Server for Home Assistant
# 🚀 MCP Server for Home Assistant - Bringing AI-Powered Smart Homes to Life!
The Model Context Protocol (MCP) Server is a robust, secure, and high-performance bridge that integrates Home Assistant with Language Learning Models (LLMs), enabling natural language control and real-time monitoring of your smart home devices. Unlock advanced automation, control, and analytics for your Home Assistant ecosystem.
![License](https://img.shields.io/badge/license-MIT-blue.svg)
![Bun](https://img.shields.io/badge/bun-%3E%3D1.0.26-black)
![TypeScript](https://img.shields.io/badge/typescript-%5E5.0.0-blue.svg)
![Test Coverage](https://img.shields.io/badge/coverage-95%25-brightgreen.svg)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![Bun](https://img.shields.io/badge/bun-%3E%3D1.0.26-black)](https://bun.sh)
[![TypeScript](https://img.shields.io/badge/typescript-%5E5.0.0-blue.svg)](https://www.typescriptlang.org)
[![Test Coverage](https://img.shields.io/badge/coverage-95%25-brightgreen.svg)](#)
[![Documentation](https://img.shields.io/badge/docs-github.io-blue.svg)](https://jango-blockchained.github.io/homeassistant-mcp/)
[![Docker](https://img.shields.io/badge/docker-%3E%3D20.10.8-blue)](https://www.docker.com)
## Table of Contents
---
- [Overview](#overview)
- [Key Features](#key-features)
- [Architecture & Design](#architecture--design)
- [Installation](#installation)
- [Basic Setup](#basic-setup)
- [Docker Setup (Recommended)](#docker-setup-recommended)
- [Usage](#usage)
- [API & Documentation](#api--documentation)
- [Development](#development)
- [Roadmap & Future Plans](#roadmap--future-plans)
- [Community & Support](#community--support)
- [Contributing](#contributing)
- [Troubleshooting & FAQ](#troubleshooting--faq)
- [License](#license)
## Overview 🌐
## Overview
Welcome to the **Model Context Protocol (MCP) Server for Home Assistant**! This robust platform bridges Home Assistant with cutting-edge Language Learning Models (LLMs), enabling natural language interactions and real-time automation of your smart devices. Imagine entering your home, saying:
The MCP Server bridges Home Assistant with advanced LLM integrations to deliver intuitive control, automation, and state monitoring. Leveraging a high-performance runtime and real-time communication protocols, MCP offers a seamless experience for managing your smart home.
> "Hey MCP, dim the lights and start my evening playlist,"
## Key Features
and watching your home transform instantly—that's the magic that MCP Server delivers!
### Device Control & Monitoring
- **Smart Device Control:** Manage lights, climate, covers, switches, sensors, media players, fans, locks, vacuums, and cameras using natural language commands.
- **Real-time Updates:** Receive instant notifications and updates via Server-Sent Events (SSE).
---
### System & Automation Management
- **Automation Engine:** Create, modify, and trigger custom automation rules with ease.
- **Add-on & Package Management:** Integrates with HACS for deploying custom integrations, themes, scripts, and applications.
- **Robust System Management:** Features advanced state monitoring, error handling, and security safeguards.
## Key Benefits ✨
## Architecture & Design
### 🎮 Device Control & Monitoring
- **Voice-Controlled Automation:**
Use simple commands like "Turn on the kitchen lights" or "Set the thermostat to 22°C" without touching a switch.
**Real-World Example:**
In the morning, say "Good morning! Open the blinds and start the coffee machine" to kickstart your day automatically.
The MCP Server is built with scalability, resilience, and security in mind:
- **Real-Time Communication:**
Experience sub-100ms latency updates via Server-Sent Events (SSE) or WebSocket connections, ensuring your dashboard is always current.
**Real-World Example:**
Monitor energy usage instantly during peak hours and adjust remotely for efficient consumption.
- **High-Performance Runtime:** Powered by Bun for fast startup, efficient memory utilization, and native TypeScript support.
- **Real-time Communication:** Employs Server-Sent Events (SSE) for continuous, real-time data updates.
- **Modular & Extensible:** Designed to support plugins, add-ons, and custom automation scripts, allowing for easy expansion.
- **Secure API Integration:** Implements token-based authentication, rate limiting, and adherence to best security practices.
- **Seamless Automation:**
Create scene-based rules to synchronize multiple devices effortlessly.
**Real-World Example:**
For movie nights, have MCP dim the lights, adjust the sound system, and launch your favorite streaming app with just one command.
For a deeper dive into the system architecture, please refer to our [Architecture Documentation](docs/architecture.md).
### 🤖 AI-Powered Enhancements
- **Natural Language Processing (NLP):**
Convert everyday speech into actionable commands—just say, "Prepare the house for dinner," and MCP will adjust lighting, temperature, and even play soft background music.
## Installation
- **Predictive Automation & Suggestions:**
Receive proactive recommendations based on usage habits and environmental trends.
**Real-World Example:**
When home temperature fluctuates unexpectedly, MCP suggests an optimal setting and notifies you immediately.
### Basic Setup
- **Anomaly Detection:**
Continuously monitor device activity and alert you to unusual behavior, helping prevent malfunctions or potential security breaches.
---
## Architectural Overview 🏗
Our architecture is engineered for performance, scalability, and security. The following Mermaid diagram illustrates the data flow and component interactions:
```mermaid
graph TD
subgraph Client
A[Client Application<br>(Web / Mobile / Voice)]
end
subgraph CDN
B[CDN / Cache]
end
subgraph Server
C[Bun Native Server]
E[NLP Engine &<br>Language Processing Module]
end
subgraph Integration
D[Home Assistant<br>(Devices, Lights, Thermostats)]
end
A -->|HTTP Request| B
B -- Cache Miss --> C
C -->|Interpret Command| E
E -->|Determine Action| D
D -->|Return State/Action| C
C -->|Response| B
B -->|Cached/Processed Response| A
```
Learn more about our architecture in the [Architecture Documentation](docs/architecture.md).
---
## Technical Stack 🔧
Our solution is built on a modern, high-performance stack that powers every feature:
- **Bun:**
A next-generation JavaScript runtime offering rapid startup times, native TypeScript support, and high performance.
👉 [Learn about Bun](https://bun.sh)
- **Bun Native Server:**
Utilizes Bun's built-in HTTP server to efficiently process API requests with sub-100ms response times.
👉 See the [Installation Guide](docs/getting-started/installation.md) for details.
- **Natural Language Processing (NLP) & LLM Integration:**
Processes and interprets natural language commands using state-of-the-art LLMs and custom NLP modules.
👉 Find API usage details in the [API Documentation](docs/api.md).
- **Home Assistant Integration:**
Provides seamless connectivity with Home Assistant, ensuring flawless communication with your smart devices.
👉 Refer to the [Usage Guide](docs/usage.md) for more information.
- **Redis Cache:**
Enables rapid data retrieval and session persistence essential for real-time updates.
- **TypeScript:**
Enhances type safety and developer productivity across the entire codebase.
- **JWT & Security Middleware:**
Protects your ecosystem with JWT-based authentication, request sanitization, rate-limiting, and encryption.
- **Containerization with Docker:**
Enables scalable, isolated deployments for production environments.
For further technical details, check out our [Documentation Index](docs/index.md).
---
## Installation 🛠
### Installing via Smithery
To install Home Assistant MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@jango-blockchained/advanced-homeassistant-mcp):
1. **Install Bun:** If Bun is not installed:
```bash
npx -y @smithery/cli install @jango-blockchained/advanced-homeassistant-mcp --client claude
```
### 🐳 Docker Setup (Recommended)
For a hassle-free, containerized deployment:
```bash
# 1. Clone the repository (using a shallow copy for efficiency)
git clone --depth 1 https://github.com/jango-blockchained/homeassistant-mcp.git
# 2. Configure your environment: copy the example file and edit it with your Home Assistant credentials
cp .env.example .env # Modify .env with your Home Assistant host, tokens, etc.
# 3. Build and run the Docker containers
docker compose up -d --build
# 4. View real-time logs (last 50 log entries)
docker compose logs -f --tail=50
```
👉 Refer to our [Installation Guide](docs/getting-started/installation.md) for full details.
### 💻 Bare Metal Installation
For direct deployment on your host machine:
```bash
# 1. Install Bun (if not already installed)
curl -fsSL https://bun.sh/install | bash
# 2. Install project dependencies with caching support
bun install --frozen-lockfile
# 3. Launch the server in development mode with hot-reload enabled
bun run dev --watch
```
2. **Clone the Repository:**
```bash
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
```
---
3. **Install Dependencies:**
```bash
bun install
```
## Real-World Usage Examples 🔍
4. **Build the Project:**
```bash
bun run build
```
### Docker Setup (Recommended)
1. **Clone the Repository:**
```bash
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
```
2. **Configure Environment:**
```bash
cp .env.example .env
```
Customize the `.env` file with your Home Assistant configuration.
3. **Deploy with Docker Compose:**
```bash
docker compose up -d
```
- View logs: `docker compose logs -f`
- Stop the server: `docker compose down`
4. **Update the Application:**
```bash
git pull && docker compose up -d --build
```
## Usage
Once the server is running, open your browser at [http://localhost:3000](http://localhost:3000). For real-time device updates, integrate the SSE endpoint in your application:
### 📱 Smart Home Dashboard Integration
Integrate MCP's real-time updates into your custom dashboard for a dynamic smart home experience:
```javascript
const eventSource = new EventSource('http://localhost:3000/subscribe_events?token=YOUR_TOKEN&domain=light');
eventSource.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('Update received:', data);
console.log('Real-time update:', data);
// Update your UI dashboard, e.g., refresh a light intensity indicator.
};
```
## API & Documentation
### 🏠 Voice-Activated Control
Utilize voice commands to trigger actions with minimal effort:
Access comprehensive API details and guides in the docs directory:
```javascript
// Establish a WebSocket connection for real-time command processing
const ws = new WebSocket('wss://mcp.yourha.com/ws');
- **API Reference:** [API Documentation](docs/api.md)
- **SSE Documentation:** [SSE API](docs/sse-api.md)
- **Troubleshooting Guide:** [Troubleshooting](docs/troubleshooting.md)
- **Architecture Details:** [Architecture Documentation](docs/architecture.md)
ws.onmessage = ({ data }) => {
const update = JSON.parse(data);
if (update.entity_id === 'light.living_room') {
console.log('Adjusting living room lighting based on voice command...');
// Additional logic to update your UI or trigger further actions can go here.
}
};
## Development
// Simulate processing a voice command
function simulateVoiceCommand(command) {
console.log("Processing voice command:", command);
// Integrate with your actual voice-to-text system as needed.
}
### Running in Development Mode
```bash
bun run dev
simulateVoiceCommand("Turn off all the lights for bedtime");
```
### Running Tests
👉 Learn more in our [Usage Guide](docs/usage.md).
- Execute all tests:
```bash
bun test
```
---
- Run tests with coverage:
```bash
bun test --coverage
```
## Update Strategy 🔄
### Production Build & Start
Maintain a seamless operation with zero downtime updates:
```bash
bun run build
bun start
# 1. Pull the latest Docker images
docker compose pull
# 2. Rebuild and restart containers smoothly
docker compose up -d --build
# 3. Clean up unused Docker images to free up space
docker system prune -f
```
## Roadmap & Future Plans
For more details, review our [Troubleshooting & Updates](docs/troubleshooting.md).
The MCP Server is under active development and improvement. Planned enhancements include:
---
- **Advanced Automation Capabilities:** Introducing more complex automation rules and conditional logic.
- **Enhanced Security Features:** Additional authentication layers, encryption enhancements, and security monitoring tools.
- **User Interface Improvements:** Development of a more intuitive web dashboard for easier device management.
- **Expanded Integrations:** Support for a wider array of smart home devices and third-party services.
- **Performance Optimizations:** Continued efforts to reduce latency and improve resource efficiency.
## Security Features 🔐
For additional details, check out our [Roadmap](docs/roadmap.md).
We prioritize the security of your smart home with multiple layers of defense:
- **JWT Authentication 🔑:** Secure, token-based API access to prevent unauthorized usage.
- **Request Sanitization 🧼:** Automatic filtering and validation of API requests to combat injection attacks.
- **Rate Limiting & Fail2Ban 🚫:** Monitors requests to prevent brute force and DDoS attacks.
- **End-to-End Encryption 🔒:** Ensures that your commands and data remain private during transmission.
## Community & Support
---
Join our community to stay updated, share ideas, and get help:
## Contributing 🤝
- **GitHub Issues:** Report bugs or suggest features on our [GitHub Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues).
- **Discussion Forums:** Connect with other users and contributors in our community forums.
- **Chat Platforms:** Join our real-time discussions on [Discord](#) or [Slack](#).
## Contributing
We welcome your contributions! To get started:
1. Fork the repository.
2. Create your feature branch:
We value community contributions! Here's how you can help improve MCP Server:
1. **Fork the Repository 🍴**
Create your own copy of the project.
2. **Create a Feature Branch 🌿**
```bash
git checkout -b feature/your-feature-name
```
3. Install dependencies:
3. **Install Dependencies & Run Tests 🧪**
```bash
bun install
bun test --coverage
```
4. Make your changes and run tests:
```bash
bun test
4. **Make Your Changes & Commit 📝**
Follow the [Conventional Commits](https://www.conventionalcommits.org) guidelines.
5. **Open a Pull Request 🔀**
Submit your changes for review.
Read more in our [Contribution Guidelines](docs/contributing.md).
---
## Roadmap & Future Enhancements 🔮
We're continuously evolving MCP Server. Upcoming features include:
- **AI Assistant Integration (Q4 2024):**
Smarter, context-aware voice commands and personalized automation.
- **Predictive Automation (Q1 2025):**
Enhanced scheduling capabilities powered by advanced AI.
- **Enhanced Security (Q2 2024):**
Introduction of multi-factor authentication, advanced monitoring, and rigorous encryption methods.
- **Performance Optimizations (Q3 2024):**
Reducing latency further, optimizing caching, and improving load balancing.
For more details, see our [Roadmap](docs/roadmap.md).
---
## Community & Support 🌍
Your feedback and collaboration are vital! Join our community:
- **GitHub Issues:** Report bugs or request features via our [Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues).
- **Discord & Slack:** Connect with fellow users and developers in real-time.
- **Documentation:** Find comprehensive guides on the [MCP Documentation Website](https://jango-blockchained.github.io/homeassistant-mcp/).
---
## License 📜
This project is licensed under the MIT License. See [LICENSE](LICENSE) for full details.
---
🔋 Batteries included.
## MCP Client Integration
This MCP server can be integrated with various clients that support the Model Context Protocol. Below are instructions for different client integrations:
### Cursor Integration
The server can be integrated with Cursor by adding the configuration to `.cursor/config/config.json`:
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": ["run", "start"],
"cwd": "${workspaceRoot}",
"env": {
"NODE_ENV": "development"
}
}
}
}
```
5. Commit and push your changes, then open a Pull Request.
For detailed guidelines, see [Contributing Guide](docs/contributing.md).
### Claude Desktop Integration
## Troubleshooting & FAQ
For Claude Desktop, add the following to your Claude configuration file:
### Common Issues
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": ["run", "start", "--port", "8080"],
"env": {
"NODE_ENV": "production"
}
}
}
}
```
- **Connection Problems:** Ensure that your `HASS_HOST`, authentication token, and WebSocket URL are correctly configured.
- **Docker Deployment:** Confirm that Docker is running and that your `.env` file contains the correct settings.
- **Automation Errors:** Verify entity availability and review your automation configurations for potential issues.
### Cline Integration
For more troubleshooting details, refer to [Troubleshooting Guide](docs/troubleshooting.md).
For Cline-based clients, add the following configuration:
### Frequently Asked Questions
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": [
"run",
"start",
"--enable-cline",
"--config",
"${configDir}/.env"
],
"env": {
"NODE_ENV": "production",
"CLINE_MODE": "true"
}
}
}
}
```
**Q: What platforms does MCP Server support?**
### Command Line Usage
A: MCP Server runs on Linux, macOS, and Windows (Docker is recommended for Windows environments).
#### Windows
A CMD script is provided in the `scripts` directory. To use it:
**Q: How do I report a bug or request a feature?**
1. Navigate to the `scripts` directory
2. Run `start_mcp.cmd`
A: Please use our [GitHub Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues) to report bugs or request new features.
**Q: Can I contribute to the project?**
A: Absolutely! We welcome contributions from the community. See the [Contributing](#contributing) section for more details.
## License
This project is licensed under the MIT License. See [LICENSE](LICENSE) for the full license text.
## Documentation
Full documentation is available at: [https://jango-blockchained.github.io/homeassistant-mcp/](https://jango-blockchained.github.io/homeassistant-mcp/)
## Quick Start
## Installation
## Usage
The script will start the MCP server with default configuration.

570
bun.lock Executable file
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}
}

BIN
bun.lockb

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64
docker-build.sh Executable file
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@@ -0,0 +1,64 @@
#!/bin/bash
# Enable error handling
set -euo pipefail
# Function to clean up on script exit
cleanup() {
echo "Cleaning up..."
docker builder prune -f --filter until=24h
docker image prune -f
}
trap cleanup EXIT
# Clean up Docker system
echo "Cleaning up Docker system..."
docker system prune -f --volumes
# Set build arguments for better performance
export DOCKER_BUILDKIT=1
export COMPOSE_DOCKER_CLI_BUILD=1
export BUILDKIT_PROGRESS=plain
# Calculate available memory and CPU
TOTAL_MEM=$(free -m | awk '/^Mem:/{print $2}')
BUILD_MEM=$(( TOTAL_MEM / 2 )) # Use half of available memory
CPU_COUNT=$(nproc)
CPU_QUOTA=$(( CPU_COUNT * 50000 )) # Allow 50% CPU usage per core
echo "Building with ${BUILD_MEM}MB memory limit and CPU quota ${CPU_QUOTA}"
# Remove any existing lockfile
rm -f bun.lockb
# Build with resource limits, optimizations, and timeout
echo "Building Docker image..."
DOCKER_BUILDKIT=1 docker build \
--memory="${BUILD_MEM}m" \
--memory-swap="${BUILD_MEM}m" \
--cpu-quota="${CPU_QUOTA}" \
--build-arg BUILDKIT_INLINE_CACHE=1 \
--build-arg DOCKER_BUILDKIT=1 \
--build-arg NODE_ENV=production \
--progress=plain \
--no-cache \
--compress \
-t homeassistant-mcp:latest \
-t homeassistant-mcp:$(date +%Y%m%d) \
.
# Check if build was successful
BUILD_EXIT_CODE=$?
if [ $BUILD_EXIT_CODE -eq 124 ]; then
echo "Build timed out after 15 minutes!"
exit 1
elif [ $BUILD_EXIT_CODE -ne 0 ]; then
echo "Build failed with exit code ${BUILD_EXIT_CODE}!"
exit 1
else
echo "Build completed successfully!"
# Show image size and layers
docker image ls homeassistant-mcp:latest --format "Image size: {{.Size}}"
echo "Layer count: $(docker history homeassistant-mcp:latest | wc -l)"
fi

68
docker/speech/Dockerfile Normal file
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# Use Python slim image as builder
FROM python:3.10-slim as builder
# Install build dependencies
RUN apt-get update && apt-get install -y \
git \
build-essential \
portaudio19-dev \
&& rm -rf /var/lib/apt/lists/*
# Create and activate virtual environment
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# Install Python dependencies with specific versions and CPU-only variants
RUN pip install --no-cache-dir "numpy>=1.24.3,<2.0.0" && \
pip install --no-cache-dir torch==2.1.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cpu && \
pip install --no-cache-dir faster-whisper==0.10.0 openwakeword==0.4.0 pyaudio==0.2.14 sounddevice==0.4.6 requests==2.31.0 && \
pip freeze > /opt/venv/requirements.txt
# Create final image
FROM python:3.10-slim
# Copy virtual environment from builder
COPY --from=builder /opt/venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
# Install audio dependencies
RUN apt-get update && apt-get install -y \
portaudio19-dev \
python3-pyaudio \
alsa-utils \
libasound2 \
libasound2-plugins \
pulseaudio \
&& rm -rf /var/lib/apt/lists/*
# Create necessary directories
RUN mkdir -p /models/wake_word /audio
# Set working directory
WORKDIR /app
# Copy the wake word detection script
COPY wake_word_detector.py .
# Set environment variables
ENV WHISPER_MODEL_PATH=/models \
WAKEWORD_MODEL_PATH=/models/wake_word \
PYTHONUNBUFFERED=1 \
ASR_MODEL=base.en \
ASR_MODEL_PATH=/models
# Add resource limits to Python
ENV PYTHONMALLOC=malloc \
MALLOC_TRIM_THRESHOLD_=100000 \
PYTHONDEVMODE=1
# Add healthcheck
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD ps aux | grep '[p]ython' || exit 1
# Copy audio setup script
COPY setup-audio.sh /setup-audio.sh
RUN chmod +x /setup-audio.sh
# Start command
CMD ["/bin/bash", "-c", "/setup-audio.sh && python -u wake_word_detector.py"]

16
docker/speech/setup-audio.sh Executable file
View File

@@ -0,0 +1,16 @@
#!/bin/bash
# Wait for PulseAudio to be ready
sleep 2
# Mute the monitor to prevent feedback
pactl set-source-mute alsa_output.pci-0000_00_1b.0.analog-stereo.monitor 1
# Set microphone sensitivity to 65%
pactl set-source-volume alsa_input.pci-0000_00_1b.0.analog-stereo 65%
# Set speaker volume to 40%
pactl set-sink-volume alsa_output.pci-0000_00_1b.0.analog-stereo 40%
# Make the script executable
chmod +x /setup-audio.sh

View File

@@ -0,0 +1,415 @@
import os
import json
import queue
import threading
import numpy as np
import sounddevice as sd
from openwakeword import Model
from datetime import datetime
import wave
from faster_whisper import WhisperModel
import requests
import logging
import time
# Set up logging
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
# Configuration
SAMPLE_RATE = 16000
CHANNELS = 1
CHUNK_SIZE = 1024
BUFFER_DURATION = 10 # seconds to keep in buffer
DETECTION_THRESHOLD = 0.5
CONTINUOUS_TRANSCRIPTION_INTERVAL = 3 # seconds between transcriptions
MAX_MODEL_LOAD_RETRIES = 3
MODEL_LOAD_RETRY_DELAY = 5 # seconds
MODEL_DOWNLOAD_TIMEOUT = 600 # 10 minutes timeout for model download
# Audio processing parameters
NOISE_THRESHOLD = 0.08 # Increased threshold for better noise filtering
MIN_SPEECH_DURATION = 2.0 # Longer minimum duration to avoid fragments
SILENCE_DURATION = 1.0 # Longer silence duration
MAX_REPETITIONS = 1 # More aggressive repetition filtering
ECHO_THRESHOLD = 0.75 # More sensitive echo detection
MIN_SEGMENT_DURATION = 1.0 # Longer minimum segment duration
FEEDBACK_WINDOW = 5 # Window size for feedback detection in seconds
# Feature flags from environment
WAKE_WORD_ENABLED = os.environ.get('ENABLE_WAKE_WORD', 'false').lower() == 'true'
SPEECH_ENABLED = os.environ.get('ENABLE_SPEECH_FEATURES', 'true').lower() == 'true'
# Wake word models to use (only if wake word is enabled)
WAKE_WORDS = ["alexa"] # Using 'alexa' as temporary replacement for 'gaja'
WAKE_WORD_ALIAS = "gaja" # What we print when wake word is detected
# Home Assistant Configuration
HASS_HOST = os.environ.get('HASS_HOST', 'http://homeassistant.local:8123')
HASS_TOKEN = os.environ.get('HASS_TOKEN')
def initialize_asr_model():
"""Initialize the ASR model with retries and timeout"""
model_path = os.environ.get('ASR_MODEL_PATH', '/models')
model_name = os.environ.get('ASR_MODEL', 'large-v3')
start_time = time.time()
for attempt in range(MAX_MODEL_LOAD_RETRIES):
try:
if time.time() - start_time > MODEL_DOWNLOAD_TIMEOUT:
logger.error("Model download timeout exceeded")
raise TimeoutError("Model download took too long")
logger.info(f"Loading ASR model (attempt {attempt + 1}/{MAX_MODEL_LOAD_RETRIES})")
model = WhisperModel(
model_size_or_path=model_name,
device="cpu",
compute_type="int8",
download_root=model_path,
num_workers=1 # Reduce concurrent downloads
)
logger.info("ASR model loaded successfully")
return model
except Exception as e:
logger.error(f"Failed to load ASR model (attempt {attempt + 1}): {e}")
if attempt < MAX_MODEL_LOAD_RETRIES - 1:
logger.info(f"Retrying in {MODEL_LOAD_RETRY_DELAY} seconds...")
time.sleep(MODEL_LOAD_RETRY_DELAY)
else:
logger.error("Failed to load ASR model after all retries")
raise
# Initialize the ASR model with retries
try:
asr_model = initialize_asr_model()
except Exception as e:
logger.error(f"Critical error initializing ASR model: {e}")
raise
def send_command_to_hass(domain, service, entity_id):
"""Send command to Home Assistant"""
if not HASS_TOKEN:
logger.error("Error: HASS_TOKEN not set")
return False
headers = {
"Authorization": f"Bearer {HASS_TOKEN}",
"Content-Type": "application/json",
}
url = f"{HASS_HOST}/api/services/{domain}/{service}"
data = {"entity_id": entity_id}
try:
response = requests.post(url, headers=headers, json=data)
response.raise_for_status()
logger.info(f"Command sent: {domain}.{service} for {entity_id}")
return True
except Exception as e:
logger.error(f"Error sending command to Home Assistant: {e}")
return False
def is_speech(audio_data, threshold=NOISE_THRESHOLD):
"""Detect if audio segment contains speech based on amplitude and frequency content"""
# Calculate RMS amplitude
rms = np.sqrt(np.mean(np.square(audio_data)))
# Calculate signal energy in speech frequency range (100-4000 Hz)
fft = np.fft.fft(audio_data)
freqs = np.fft.fftfreq(len(audio_data), 1/SAMPLE_RATE)
speech_mask = (np.abs(freqs) >= 100) & (np.abs(freqs) <= 4000)
speech_energy = np.sum(np.abs(fft[speech_mask])) / len(audio_data)
# Enhanced echo detection
# 1. Check for periodic patterns in the signal
autocorr = np.correlate(audio_data, audio_data, mode='full')
autocorr = autocorr[len(autocorr)//2:] # Use only positive lags
peaks = np.where(autocorr > ECHO_THRESHOLD * np.max(autocorr))[0]
peak_spacing = np.diff(peaks)
has_periodic_echo = len(peak_spacing) > 2 and np.std(peak_spacing) < 0.1 * np.mean(peak_spacing)
# 2. Check for sudden amplitude changes
amplitude_envelope = np.abs(audio_data)
amplitude_changes = np.diff(amplitude_envelope)
has_feedback_spikes = np.any(np.abs(amplitude_changes) > threshold * 2)
# 3. Check frequency distribution
freq_magnitudes = np.abs(fft)[:len(fft)//2]
peak_freqs = freqs[:len(fft)//2][np.argsort(freq_magnitudes)[-3:]]
has_feedback_freqs = np.any((peak_freqs > 2000) & (peak_freqs < 4000))
# Combine all criteria
is_valid_speech = (
rms > threshold and
speech_energy > threshold and
not has_periodic_echo and
not has_feedback_spikes and
not has_feedback_freqs
)
return is_valid_speech
def process_command(text):
"""Process the transcribed command and execute appropriate action"""
text = text.lower().strip()
# Skip if text is too short or contains numbers (likely noise)
if len(text) < 5 or any(char.isdigit() for char in text):
logger.debug("Text too short or contains numbers, skipping")
return
# Enhanced noise pattern detection
noise_patterns = ["lei", "los", "und", "aber", "nicht mehr", "das das", "und und"]
for pattern in noise_patterns:
if text.count(pattern) > 1: # More aggressive pattern filtering
logger.debug(f"Detected noise pattern '{pattern}', skipping")
return
# More aggressive repetition detection
words = text.split()
if len(words) >= 2:
# Check for immediate word repetitions
for i in range(len(words)-1):
if words[i] == words[i+1]:
logger.debug(f"Detected immediate word repetition: '{words[i]}', skipping")
return
# Check for phrase repetitions
phrases = [' '.join(words[i:i+2]) for i in range(len(words)-1)]
phrase_counts = {}
for phrase in phrases:
phrase_counts[phrase] = phrase_counts.get(phrase, 0) + 1
if phrase_counts[phrase] > MAX_REPETITIONS:
logger.debug(f"Skipping due to excessive repetition: '{phrase}'")
return
# German command mappings
commands = {
"ausschalten": "turn_off",
"einschalten": "turn_on",
"an": "turn_on",
"aus": "turn_off"
}
rooms = {
"wohnzimmer": "living_room",
"küche": "kitchen",
"schlafzimmer": "bedroom",
"bad": "bathroom"
}
# Detect room
detected_room = None
for german_room, english_room in rooms.items():
if german_room in text:
detected_room = english_room
break
# Detect command
detected_command = None
for german_cmd, english_cmd in commands.items():
if german_cmd in text:
detected_command = english_cmd
break
if detected_room and detected_command:
# Construct entity ID (assuming light)
entity_id = f"light.{detected_room}"
# Send command to Home Assistant
if send_command_to_hass("light", detected_command, entity_id):
logger.info(f"Executed: {detected_command} for {entity_id}")
else:
logger.error("Failed to execute command")
else:
logger.debug(f"No command found in text: '{text}'")
class AudioProcessor:
def __init__(self):
logger.info("Initializing AudioProcessor...")
self.audio_buffer = queue.Queue()
self.recording = False
self.buffer = np.zeros(SAMPLE_RATE * BUFFER_DURATION)
self.buffer_lock = threading.Lock()
self.last_transcription_time = 0
self.stream = None
self.speech_detected = False
self.silence_frames = 0
self.speech_frames = 0
# Initialize wake word detection only if enabled
if WAKE_WORD_ENABLED:
try:
logger.info("Initializing wake word model...")
self.wake_word_model = Model(vad_threshold=0.5)
self.last_prediction = None
logger.info("Wake word model initialized successfully")
except Exception as e:
logger.error(f"Failed to initialize wake word model: {e}")
raise
else:
self.wake_word_model = None
self.last_prediction = None
logger.info("Wake word detection disabled")
def should_transcribe(self):
"""Determine if we should transcribe based on mode and timing"""
current_time = datetime.now().timestamp()
if not WAKE_WORD_ENABLED:
# Check if enough time has passed since last transcription
time_since_last = current_time - self.last_transcription_time
if time_since_last >= CONTINUOUS_TRANSCRIPTION_INTERVAL:
# Only transcribe if we detect speech
frames_per_chunk = CHUNK_SIZE
min_speech_frames = int(MIN_SPEECH_DURATION * SAMPLE_RATE / frames_per_chunk)
if self.speech_frames >= min_speech_frames:
self.last_transcription_time = current_time
self.speech_frames = 0 # Reset counter
return True
return False
def audio_callback(self, indata, frames, time, status):
"""Callback for audio input"""
if status:
logger.warning(f"Audio callback status: {status}")
# Convert to mono if necessary
if CHANNELS > 1:
audio_data = np.mean(indata, axis=1)
else:
audio_data = indata.flatten()
# Check for speech
if is_speech(audio_data):
self.speech_frames += 1
self.silence_frames = 0
else:
self.silence_frames += 1
frames_per_chunk = CHUNK_SIZE
silence_frames_threshold = int(SILENCE_DURATION * SAMPLE_RATE / frames_per_chunk)
if self.silence_frames >= silence_frames_threshold:
self.speech_frames = 0
# Update circular buffer
with self.buffer_lock:
self.buffer = np.roll(self.buffer, -len(audio_data))
self.buffer[-len(audio_data):] = audio_data
if WAKE_WORD_ENABLED:
# Process for wake word detection
self.last_prediction = self.wake_word_model.predict(audio_data)
# Check if wake word detected
for wake_word in WAKE_WORDS:
confidence = self.last_prediction[wake_word]
if confidence > DETECTION_THRESHOLD:
logger.info(
f"Wake word: {WAKE_WORD_ALIAS} (confidence: {confidence:.2f})"
)
self.process_audio()
break
else:
# Continuous transcription mode
if self.should_transcribe():
self.process_audio()
def process_audio(self):
"""Process the current audio buffer (save and transcribe)"""
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"/audio/audio_segment_{timestamp}.wav"
# Save the audio buffer to a WAV file
with wave.open(filename, 'wb') as wf:
wf.setnchannels(CHANNELS)
wf.setsampwidth(2) # 16-bit audio
wf.setframerate(SAMPLE_RATE)
# Convert float32 to int16
audio_data = (self.buffer * 32767).astype(np.int16)
wf.writeframes(audio_data.tobytes())
logger.info(f"Saved audio segment to {filename}")
# Transcribe the audio with German language preference
try:
segments, info = asr_model.transcribe(
filename,
language="de", # Set German as preferred language
beam_size=5,
temperature=0
)
# Get the full transcribed text
transcribed_text = " ".join(segment.text for segment in segments)
logger.info(f"Transcribed text: {transcribed_text}")
# Process the command
process_command(transcribed_text)
except Exception as e:
logger.error(f"Error during transcription or processing: {e}")
def start(self):
"""Start audio processing"""
try:
logger.info("Starting audio processor...")
# Log configuration
logger.debug(f"Sample Rate: {SAMPLE_RATE}")
logger.debug(f"Channels: {CHANNELS}")
logger.debug(f"Chunk Size: {CHUNK_SIZE}")
logger.debug(f"Buffer Duration: {BUFFER_DURATION}")
logger.debug(f"Wake Word Enabled: {WAKE_WORD_ENABLED}")
logger.debug(f"Speech Enabled: {SPEECH_ENABLED}")
logger.debug(f"ASR Model: {os.environ.get('ASR_MODEL')}")
if WAKE_WORD_ENABLED:
logger.info("Initializing wake word detection...")
logger.info(f"Loaded wake words: {', '.join(WAKE_WORDS)}")
else:
logger.info("Starting continuous transcription mode...")
interval = CONTINUOUS_TRANSCRIPTION_INTERVAL
logger.info(f"Will transcribe every {interval} seconds")
try:
logger.debug("Setting up audio input stream...")
with sd.InputStream(
channels=CHANNELS,
samplerate=SAMPLE_RATE,
blocksize=CHUNK_SIZE,
callback=self.audio_callback
):
logger.info("Audio input stream started successfully")
logger.info("Listening for audio input...")
logger.info("Press Ctrl+C to stop")
while True:
sd.sleep(1000) # Sleep for 1 second
except sd.PortAudioError as e:
logger.error(f"Error setting up audio stream: {e}")
logger.error("Check if microphone is connected and accessible")
raise
except Exception as e:
logger.error(f"Unexpected error in audio stream: {e}")
raise
except KeyboardInterrupt:
logger.info("\nStopping audio processing...")
except Exception as e:
logger.error("Critical error in audio processing", exc_info=True)
raise
if __name__ == "__main__":
try:
logger.info("Initializing AudioProcessor...")
processor = AudioProcessor()
processor.start()
except Exception as e:
logger.error("Failed to start AudioProcessor", exc_info=True)
raise

View File

@@ -4,6 +4,9 @@ gem "github-pages", group: :jekyll_plugins
gem "jekyll-theme-minimal"
gem "jekyll-relative-links"
gem "jekyll-seo-tag"
gem "jekyll-remote-theme"
gem "jekyll-github-metadata"
gem "faraday-retry"
# Windows and JRuby does not include zoneinfo files, so bundle the tzinfo-data gem
# and associated library.
@@ -15,3 +18,6 @@ end
# Lock `http_parser.rb` gem to `v0.6.x` on JRuby builds since newer versions of the gem
# do not have a Java counterpart.
gem "http_parser.rb", "~> 0.6.0", :platforms => [:jruby]
# Add webrick for Ruby 3.0+
gem "webrick", "~> 1.7"

View File

@@ -1,20 +0,0 @@
# Home Assistant MCP Documentation
Welcome to the documentation for the Home Assistant MCP (Model Context Protocol) Server. Here you'll find comprehensive guides on setup, configuration, usage, and contribution.
## Quick Navigation
- [Getting Started Guide](getting-started.md)
- [API Documentation](api.md)
- [Troubleshooting](troubleshooting.md)
- [Contributing Guide](contributing.md)
## Repository Links
- [GitHub Repository](https://github.com/jango-blockchained/homeassistant-mcp)
- [Issue Tracker](https://github.com/jango-blockchained/homeassistant-mcp/issues)
- [GitHub Discussions](https://github.com/jango-blockchained/homeassistant-mcp/discussions)
## License
This project is licensed under the MIT License. See [LICENSE](../LICENSE) for details.

View File

@@ -2,9 +2,24 @@ title: Model Context Protocol (MCP)
description: A bridge between Home Assistant and Language Learning Models
theme: jekyll-theme-minimal
markdown: kramdown
# Repository settings
repository: jango-blockchained/advanced-homeassistant-mcp
github: [metadata]
# Add base URL and URL settings
baseurl: "/advanced-homeassistant-mcp" # the subpath of your site
url: "https://jango-blockchained.github.io" # the base hostname & protocol
# Theme settings
logo: /assets/img/logo.png # path to logo (create this if you want a logo)
show_downloads: true # show download buttons for your repo
plugins:
- jekyll-relative-links
- jekyll-seo-tag
- jekyll-remote-theme
- jekyll-github-metadata
# Enable relative links
relative_links:
@@ -16,7 +31,39 @@ header_pages:
- index.md
- getting-started.md
- api.md
- usage.md
- tools/tools.md
- development/development.md
- troubleshooting.md
- contributing.md
- roadmap.md
# Collections
collections:
tools:
output: true
permalink: /:collection/:name
development:
output: true
permalink: /:collection/:name
# Default layouts
defaults:
- scope:
path: ""
type: "pages"
values:
layout: "default"
- scope:
path: "tools"
type: "tools"
values:
layout: "default"
- scope:
path: "development"
type: "development"
values:
layout: "default"
# Exclude files from processing
exclude:
@@ -24,3 +71,8 @@ exclude:
- Gemfile.lock
- node_modules
- vendor
# Sass settings
sass:
style: compressed
sass_dir: _sass

View File

@@ -1,6 +1,191 @@
# API Documentation
# 🚀 Home Assistant MCP API Documentation
This section details the available API endpoints for the Home Assistant MCP Server.
![API Version](https://img.shields.io/badge/API-v2.1-blueviolet) ![Rate Limit](https://img.shields.io/badge/Rate%20Limit-100%2Fmin-brightgreen)
## 🌟 Quick Start
```bash
# Get API schema with caching
curl -X GET http://localhost:3000/mcp \
-H "Cache-Control: max-age=3600" # Cache for 1 hour
```
## 🔌 Core Functions ⚙️
### State Management (`/api/state`)
```http
GET /api/state?cache=true # Enable client-side caching
POST /api/state
```
**Example Request:**
```json
{
"context": "living_room",
"state": {
"lights": "on",
"temperature": 22
},
"_cache": { // Optional caching config
"ttl": 300, // 5 minutes
"tags": ["lights", "climate"]
}
}
```
## ⚡ Action Endpoints
### Execute Action with Cache Validation
```http
POST /api/action
If-None-Match: "etag_value" // Prevent duplicate actions
```
**Batch Processing:**
```json
{
"actions": [
{ "action": "🌞 Morning Routine", "params": { "brightness": 80 } },
{ "action": "❄️ AC Control", "params": { "temp": 21 } }
],
"_parallel": true // Execute actions concurrently
}
```
## 🔍 Query Functions
### Available Actions with ETag
```http
GET /api/actions
ETag: "a1b2c3d4" // Client-side cache validation
```
**Response Headers:**
```
Cache-Control: public, max-age=86400 // 24-hour cache
ETag: "a1b2c3d4"
```
## 🌐 WebSocket Events
```javascript
const ws = new WebSocket('wss://ha-mcp/ws');
ws.onmessage = ({ data }) => {
const event = JSON.parse(data);
if(event.type === 'STATE_UPDATE') {
updateUI(event.payload); // 🎨 Real-time UI sync
}
};
```
## 🗃️ Caching Strategies
### Client-Side Caching
```http
GET /api/devices
Cache-Control: max-age=300, stale-while-revalidate=60
```
### Server-Side Cache-Control
```typescript
// Example middleware configuration
app.use(
cacheMiddleware({
ttl: 60 * 5, // 5 minutes
paths: ['/api/devices', '/mcp'],
vary: ['Authorization'] // User-specific caching
})
);
```
## ❌ Error Handling
**429 Too Many Requests:**
```json
{
"error": {
"code": "RATE_LIMITED",
"message": "Slow down! 🐢",
"retry_after": 30,
"docs": "https://ha-mcp/docs/rate-limits"
}
}
```
## 🚦 Rate Limiting Tiers
| Tier | Requests/min | Features |
|---------------|--------------|------------------------|
| Guest | 10 | Basic read-only |
| User | 100 | Full access |
| Power User | 500 | Priority queue |
| Integration | 1000 | Bulk operations |
## 🛠️ Example Usage
### Smart Cache Refresh
```javascript
async function getDevices() {
const response = await fetch('/api/devices', {
headers: {
'If-None-Match': localStorage.getItem('devicesETag')
}
});
if(response.status === 304) { // Not Modified
return JSON.parse(localStorage.devicesCache);
}
const data = await response.json();
localStorage.setItem('devicesETag', response.headers.get('ETag'));
localStorage.setItem('devicesCache', JSON.stringify(data));
return data;
}
```
## 🔒 Security Middleware (Enhanced)
### Cache-Aware Rate Limiting
```typescript
app.use(
rateLimit({
windowMs: 15 * 60 * 1000, // 15 minutes
max: 100, // Limit each IP to 100 requests per window
cache: new RedisStore(), // Distributed cache
keyGenerator: (req) => {
return `${req.ip}-${req.headers.authorization}`;
}
})
);
```
### Security Headers
```http
Content-Security-Policy: default-src 'self';
Strict-Transport-Security: max-age=31536000;
X-Content-Type-Options: nosniff;
Cache-Control: public, max-age=600;
ETag: "abc123"
```
## 📘 Best Practices
1. **Cache Wisely:** Use `ETag` and `Cache-Control` headers for state data
2. **Batch Operations:** Combine requests using `/api/actions/batch`
3. **WebSocket First:** Prefer real-time updates over polling
4. **Error Recovery:** Implement exponential backoff with jitter
5. **Cache Invalidation:** Use tags for bulk invalidation
```mermaid
graph LR
A[Client] -->|Cached Request| B{CDN}
B -->|Cache Hit| C[Return 304]
B -->|Cache Miss| D[Origin Server]
D -->|Response| B
B -->|Response| A
```
> Pro Tip: Use `curl -I` to inspect cache headers! 🔍
## Device Control
@@ -85,7 +270,7 @@ This section details the available API endpoints for the Home Assistant MCP Serv
## Automation Management
For automation management details and endpoints, please refer to the [Tools Documentation](tools/README.md).
For automation management details and endpoints, please refer to the [Tools Documentation](tools/tools.md).
## Security Considerations

326
docs/api/core.md Normal file
View File

@@ -0,0 +1,326 @@
---
layout: default
title: Core Functions
parent: API Reference
nav_order: 3
---
# Core Functions API 🔧
The Core Functions API provides the fundamental operations for interacting with Home Assistant devices and services through MCP Server.
## Device Control
### Get Device State
Retrieve the current state of devices.
```http
GET /api/state
GET /api/state/{entity_id}
```
Parameters:
- `entity_id` (optional): Specific device ID to query
```bash
# Get all states
curl http://localhost:3000/api/state
# Get specific device state
curl http://localhost:3000/api/state/light.living_room
```
Response:
```json
{
"entity_id": "light.living_room",
"state": "on",
"attributes": {
"brightness": 255,
"color_temp": 370,
"friendly_name": "Living Room Light"
},
"last_changed": "2024-01-20T15:30:00Z"
}
```
### Control Device
Execute device commands.
```http
POST /api/device/control
```
Request body:
```json
{
"entity_id": "light.living_room",
"action": "turn_on",
"parameters": {
"brightness": 200,
"color_temp": 400
}
}
```
Available actions:
- `turn_on`
- `turn_off`
- `toggle`
- `set_value`
Example with curl:
```bash
curl -X POST http://localhost:3000/api/device/control \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_JWT_TOKEN" \
-d '{
"entity_id": "light.living_room",
"action": "turn_on",
"parameters": {
"brightness": 200
}
}'
```
## Natural Language Commands
### Execute Command
Process natural language commands.
```http
POST /api/command
```
Request body:
```json
{
"command": "Turn on the living room lights and set them to 50% brightness"
}
```
Example usage:
```bash
curl -X POST http://localhost:3000/api/command \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_JWT_TOKEN" \
-d '{
"command": "Turn on the living room lights and set them to 50% brightness"
}'
```
Response:
```json
{
"success": true,
"actions": [
{
"entity_id": "light.living_room",
"action": "turn_on",
"parameters": {
"brightness": 127
},
"status": "completed"
}
],
"message": "Command executed successfully"
}
```
## Scene Management
### Create Scene
Define a new scene with multiple actions.
```http
POST /api/scene
```
Request body:
```json
{
"name": "Movie Night",
"description": "Perfect lighting for movie watching",
"actions": [
{
"entity_id": "light.living_room",
"action": "turn_on",
"parameters": {
"brightness": 50,
"color_temp": 500
}
},
{
"entity_id": "cover.living_room",
"action": "close"
}
]
}
```
### Activate Scene
Trigger a predefined scene.
```http
POST /api/scene/{scene_name}/activate
```
Example:
```bash
curl -X POST http://localhost:3000/api/scene/movie_night/activate \
-H "Authorization: Bearer YOUR_JWT_TOKEN"
```
## Groups
### Create Device Group
Create a group of devices for collective control.
```http
POST /api/group
```
Request body:
```json
{
"name": "Living Room",
"entities": [
"light.living_room_main",
"light.living_room_accent",
"switch.living_room_fan"
]
}
```
### Control Group
Control multiple devices in a group.
```http
POST /api/group/{group_name}/control
```
Request body:
```json
{
"action": "turn_off"
}
```
## System Operations
### Health Check
Check server status and connectivity.
```http
GET /health
```
Response:
```json
{
"status": "healthy",
"version": "1.0.0",
"uptime": 3600,
"homeAssistant": {
"connected": true,
"version": "2024.1.0"
}
}
```
### Configuration
Get current server configuration.
```http
GET /api/config
```
Response:
```json
{
"server": {
"port": 3000,
"host": "0.0.0.0",
"version": "1.0.0"
},
"homeAssistant": {
"url": "http://homeassistant:8123",
"connected": true
},
"features": {
"nlp": true,
"scenes": true,
"groups": true
}
}
```
## Error Handling
All endpoints follow standard HTTP status codes and return detailed error messages:
```json
{
"error": true,
"code": "INVALID_ENTITY",
"message": "Device 'light.nonexistent' not found",
"details": {
"entity_id": "light.nonexistent",
"available_entities": [
"light.living_room",
"light.kitchen"
]
}
}
```
Common error codes:
- `INVALID_ENTITY`: Device not found
- `INVALID_ACTION`: Unsupported action
- `INVALID_PARAMETERS`: Invalid command parameters
- `AUTHENTICATION_ERROR`: Invalid or missing token
- `CONNECTION_ERROR`: Home Assistant connection issue
## TypeScript Interfaces
```typescript
interface DeviceState {
entity_id: string;
state: string;
attributes: Record<string, any>;
last_changed: string;
}
interface DeviceCommand {
entity_id: string;
action: 'turn_on' | 'turn_off' | 'toggle' | 'set_value';
parameters?: Record<string, any>;
}
interface Scene {
name: string;
description?: string;
actions: DeviceCommand[];
}
interface Group {
name: string;
entities: string[];
}
```
## Related Resources
- [API Overview](index.md)
- [SSE API](sse.md)
- [Architecture](../architecture.md)
- [Examples](https://github.com/jango-blockchained/advanced-homeassistant-mcp/tree/main/examples)

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---
layout: default
title: API Overview
parent: API Reference
nav_order: 1
has_children: false
---
# API Documentation 📚
Welcome to the MCP Server API documentation. This guide covers all available endpoints, authentication methods, and integration patterns.
## API Overview
The MCP Server provides several API categories:
1. **Core API** - Basic device control and state management
2. **SSE API** - Real-time event subscriptions
3. **Scene API** - Scene management and automation
4. **Voice API** - Natural language command processing
## Authentication
All API endpoints require authentication using JWT tokens:
```bash
# Include the token in your requests
curl -H "Authorization: Bearer YOUR_JWT_TOKEN" http://localhost:3000/api/state
```
To obtain a token:
```bash
curl -X POST http://localhost:3000/auth/token \
-H "Content-Type: application/json" \
-d '{"username": "your_username", "password": "your_password"}'
```
## Core Endpoints
### Device State
```http
GET /api/state
```
Retrieve the current state of all devices:
```bash
curl http://localhost:3000/api/state
```
Response:
```json
{
"devices": [
{
"id": "light.living_room",
"state": "on",
"attributes": {
"brightness": 255,
"color_temp": 370
}
}
]
}
```
### Command Execution
```http
POST /api/command
```
Execute a natural language command:
```bash
curl -X POST http://localhost:3000/api/command \
-H "Content-Type: application/json" \
-d '{"command": "Turn on the kitchen lights"}'
```
Response:
```json
{
"success": true,
"action": "turn_on",
"device": "light.kitchen",
"message": "Kitchen lights turned on"
}
```
## Real-Time Events
### Event Subscription
```http
GET /subscribe_events
```
Subscribe to device state changes:
```javascript
const eventSource = new EventSource('http://localhost:3000/subscribe_events?token=YOUR_TOKEN');
eventSource.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('State changed:', data);
};
```
### Filtered Subscriptions
Subscribe to specific device types:
```http
GET /subscribe_events?domain=light
GET /subscribe_events?entity_id=light.living_room
```
## Scene Management
### Create Scene
```http
POST /api/scene
```
Create a new scene:
```bash
curl -X POST http://localhost:3000/api/scene \
-H "Content-Type: application/json" \
-d '{
"name": "Movie Night",
"actions": [
{"device": "light.living_room", "action": "dim", "value": 20},
{"device": "media_player.tv", "action": "on"}
]
}'
```
### Activate Scene
```http
POST /api/scene/activate
```
Activate an existing scene:
```bash
curl -X POST http://localhost:3000/api/scene/activate \
-H "Content-Type: application/json" \
-d '{"name": "Movie Night"}'
```
## Error Handling
The API uses standard HTTP status codes:
- `200` - Success
- `400` - Bad Request
- `401` - Unauthorized
- `404` - Not Found
- `500` - Server Error
Error responses include detailed messages:
```json
{
"error": true,
"message": "Device not found",
"code": "DEVICE_NOT_FOUND",
"details": {
"device_id": "light.nonexistent"
}
}
```
## Rate Limiting
API requests are rate-limited to prevent abuse:
```http
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 99
X-RateLimit-Reset: 1640995200
```
When exceeded, returns `429 Too Many Requests`:
```json
{
"error": true,
"message": "Rate limit exceeded",
"reset": 1640995200
}
```
## WebSocket API
For bi-directional communication:
```javascript
const ws = new WebSocket('ws://localhost:3000/ws');
ws.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('Received:', data);
};
ws.send(JSON.stringify({
type: 'command',
payload: {
command: 'Turn on lights'
}
}));
```
## API Versioning
The current API version is v1. Include the version in the URL:
```http
/api/v1/state
/api/v1/command
```
## Further Reading
- [SSE API Details](sse.md) - In-depth SSE documentation
- [Core Functions](core.md) - Detailed endpoint documentation
- [Architecture Overview](../architecture.md) - System design details
- [Troubleshooting](../troubleshooting.md) - Common issues and solutions

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---
layout: default
title: SSE API
parent: API Reference
nav_order: 2
---
# Server-Sent Events (SSE) API 📡
The SSE API provides real-time updates about device states and events from your Home Assistant setup. This guide covers how to use and implement SSE connections in your applications.
## Overview
Server-Sent Events (SSE) is a standard that enables servers to push real-time updates to clients over HTTP connections. MCP Server uses SSE to provide:
- Real-time device state updates
- Event notifications
- System status changes
- Command execution results
## Basic Usage
### Establishing a Connection
Create an EventSource connection to receive updates:
```javascript
const eventSource = new EventSource('http://localhost:3000/subscribe_events?token=YOUR_JWT_TOKEN');
eventSource.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('Received update:', data);
};
```
### Connection States
Handle different connection states:
```javascript
eventSource.onopen = () => {
console.log('Connection established');
};
eventSource.onerror = (error) => {
console.error('Connection error:', error);
// Implement reconnection logic if needed
};
```
## Event Types
### Device State Events
Subscribe to all device state changes:
```javascript
const stateEvents = new EventSource('http://localhost:3000/subscribe_events?type=state');
stateEvents.onmessage = (event) => {
const state = JSON.parse(event.data);
console.log('Device state changed:', state);
};
```
Example state event:
```json
{
"type": "state_changed",
"entity_id": "light.living_room",
"state": "on",
"attributes": {
"brightness": 255,
"color_temp": 370
},
"timestamp": "2024-01-20T15:30:00Z"
}
```
### Filtered Subscriptions
#### By Domain
Subscribe to specific device types:
```javascript
// Subscribe to only light events
const lightEvents = new EventSource('http://localhost:3000/subscribe_events?domain=light');
// Subscribe to multiple domains
const multiEvents = new EventSource('http://localhost:3000/subscribe_events?domain=light,switch,sensor');
```
#### By Entity ID
Subscribe to specific devices:
```javascript
// Single entity
const livingRoomLight = new EventSource(
'http://localhost:3000/subscribe_events?entity_id=light.living_room'
);
// Multiple entities
const kitchenDevices = new EventSource(
'http://localhost:3000/subscribe_events?entity_id=light.kitchen,switch.coffee_maker'
);
```
## Advanced Usage
### Connection Management
Implement robust connection handling:
```javascript
class SSEManager {
constructor(url, options = {}) {
this.url = url;
this.options = {
maxRetries: 3,
retryDelay: 1000,
...options
};
this.retryCount = 0;
this.connect();
}
connect() {
this.eventSource = new EventSource(this.url);
this.eventSource.onopen = () => {
this.retryCount = 0;
console.log('Connected to SSE stream');
};
this.eventSource.onerror = (error) => {
this.handleError(error);
};
this.eventSource.onmessage = (event) => {
this.handleMessage(event);
};
}
handleError(error) {
console.error('SSE Error:', error);
this.eventSource.close();
if (this.retryCount < this.options.maxRetries) {
this.retryCount++;
setTimeout(() => {
console.log(`Retrying connection (${this.retryCount}/${this.options.maxRetries})`);
this.connect();
}, this.options.retryDelay * this.retryCount);
}
}
handleMessage(event) {
try {
const data = JSON.parse(event.data);
// Handle the event data
console.log('Received:', data);
} catch (error) {
console.error('Error parsing SSE data:', error);
}
}
disconnect() {
if (this.eventSource) {
this.eventSource.close();
}
}
}
// Usage
const sseManager = new SSEManager('http://localhost:3000/subscribe_events?token=YOUR_TOKEN');
```
### Event Filtering
Filter events on the client side:
```javascript
class EventFilter {
constructor(conditions) {
this.conditions = conditions;
}
matches(event) {
return Object.entries(this.conditions).every(([key, value]) => {
if (Array.isArray(value)) {
return value.includes(event[key]);
}
return event[key] === value;
});
}
}
// Usage
const filter = new EventFilter({
domain: ['light', 'switch'],
state: 'on'
});
eventSource.onmessage = (event) => {
const data = JSON.parse(event.data);
if (filter.matches(data)) {
console.log('Matched event:', data);
}
};
```
## Best Practices
1. **Authentication**
- Always include authentication tokens
- Implement token refresh mechanisms
- Handle authentication errors gracefully
2. **Error Handling**
- Implement progressive retry logic
- Log connection issues
- Notify users of connection status
3. **Resource Management**
- Close EventSource connections when not needed
- Limit the number of concurrent connections
- Use filtered subscriptions when possible
4. **Performance**
- Process events efficiently
- Batch UI updates
- Consider debouncing frequent updates
## Common Issues
### Connection Drops
If the connection drops, the EventSource will automatically attempt to reconnect. You can customize this behavior:
```javascript
eventSource.addEventListener('error', (error) => {
if (eventSource.readyState === EventSource.CLOSED) {
// Connection closed, implement custom retry logic
}
});
```
### Memory Leaks
Always clean up EventSource connections:
```javascript
// In a React component
useEffect(() => {
const eventSource = new EventSource('http://localhost:3000/subscribe_events');
return () => {
eventSource.close(); // Cleanup on unmount
};
}, []);
```
## Related Resources
- [API Overview](index.md)
- [Core Functions](core.md)
- [WebSocket API](index.md#websocket-api)
- [Troubleshooting](../troubleshooting.md)

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# Architecture Documentation for MCP Server
---
layout: default
title: Architecture
nav_order: 4
---
## Overview
# Architecture Overview 🏗️
The MCP Server is designed as a high-performance, secure, and scalable bridge between Home Assistant and Language Learning Models (LLMs). This document outlines the architectural design principles, core components, and deployment strategies that power the MCP Server.
This document describes the architecture of the MCP Server, explaining how different components work together to provide a bridge between Home Assistant and Language Learning Models.
## Key Architectural Components
## System Architecture
### High-Performance Runtime with Bun
```mermaid
graph TD
subgraph "Client Layer"
WC[Web Clients]
MC[Mobile Clients]
VC[Voice Assistants]
end
- **Fast Startup & Efficiency:** Powered by Bun, the MCP Server benefits from rapid startup times, efficient memory utilization, and native TypeScript support.
- **Optimized Build Process:** Bun's build tools allow for quick iteration and deployment, ensuring minimal downtime and swift performance enhancement.
subgraph "MCP Server"
API[API Gateway]
NLP[NLP Engine]
SSE[SSE Manager]
WS[WebSocket Server]
CM[Command Manager]
SC[Scene Controller]
Cache[Redis Cache]
end
### Real-time Communication using Server-Sent Events (SSE)
subgraph "Home Assistant"
HA[Home Assistant Core]
Dev[Devices & Services]
end
- **Continuous Updates:** The server leverages SSE to deliver real-time notifications and updates, ensuring that any changes in Home Assistant are immediately communicated to connected clients.
- **Scalable Connection Handling:** SSE provides an event-driven model that efficiently manages multiple simultaneous client connections.
subgraph "AI Layer"
LLM[Language Models]
IC[Intent Classifier]
NER[Named Entity Recognition]
end
### Modular & Extensible Design
WC --> |HTTP/WS| API
MC --> |HTTP/WS| API
VC --> |HTTP| API
- **Plugin Architecture:** Designed with modularity in mind, the MCP Server supports plugins, add-ons, and custom automation scripts, enabling seamless feature expansion without disrupting core functionality.
- **Separation of Concerns:** Different components, such as device management, automation control, and system monitoring, are clearly separated, allowing independent development, testing, and scaling.
API --> |Events| SSE
API --> |Real-time| WS
API --> |Process| NLP
### Secure API Integration
NLP --> |Query| LLM
NLP --> |Extract| IC
NLP --> |Identify| NER
- **Token-Based Authentication:** Robust token-based authentication mechanisms restrict access to authorized users and systems.
- **Rate Limiting & Error Handling:** Integrated rate limiting combined with comprehensive error handling ensures system stability and prevents misuse.
- **Best Practices:** All API endpoints follow industry-standard security guidelines to protect data and maintain system integrity.
CM --> |Execute| HA
HA --> |Control| Dev
### Deployment & Scalability
SSE --> |State Updates| WC
SSE --> |State Updates| MC
WS --> |Bi-directional| WC
- **Containerized Deployment with Docker:** The use of Docker Compose enables straightforward deployment, management, and scaling of the server and its dependencies.
- **Flexible Environment Configuration:** Environment variables and configuration files (.env) facilitate smooth transitions between development, testing, and production setups.
Cache --> |Fast Access| API
HA --> |Events| Cache
```
## Future Enhancements
## Component Details
- **Advanced Automation Logic:** Integration of more complex automation rules and conditional decision-making capabilities.
- **Enhanced Security Measures:** Additional layers of security, such as multi-factor authentication and improved encryption techniques, are on the roadmap.
- **Improved Monitoring & Analytics:** Future updates will introduce advanced performance metrics and real-time analytics to monitor system health and user interactions.
### 1. Client Layer
## Conclusion
The client layer consists of various interfaces that interact with the MCP Server:
The architecture of the MCP Server prioritizes performance, scalability, and security. By leveraging Bun's high-performance runtime, employing real-time communication through SSE, and maintaining a modular, secure design, the MCP Server provides a robust platform for integrating Home Assistant with modern LLM functionalities.
- **Web Clients**: Browser-based dashboards and control panels
- **Mobile Clients**: Native mobile applications
- **Voice Assistants**: Voice-enabled devices and interfaces
*This document is a living document and will be updated as the system evolves.*
### 2. MCP Server Core
## Key Components
#### API Gateway
- Handles all incoming HTTP requests
- Manages authentication and rate limiting
- Routes requests to appropriate handlers
- **API Module:** Handles RESTful endpoints, authentication, and error management.
- **SSE Module:** Provides real-time updates through Server-Sent Events.
- **Tools Module:** Offers various utilities for device control, automation, and data processing.
- **Security Module:** Implements token-based authentication and secure communications.
- **Integration Module:** Bridges data between Home Assistant and external systems.
```typescript
interface APIGateway {
authenticate(): Promise<boolean>;
rateLimit(): Promise<boolean>;
route(request: Request): Promise<Response>;
}
```
#### NLP Engine
- Processes natural language commands
- Integrates with Language Models
- Extracts intents and entities
```typescript
interface NLPEngine {
processCommand(text: string): Promise<CommandIntent>;
extractEntities(text: string): Promise<Entity[]>;
validateIntent(intent: CommandIntent): boolean;
}
```
#### Event Management
- **SSE Manager**: Handles Server-Sent Events
- **WebSocket Server**: Manages bi-directional communication
- **Command Manager**: Processes and executes commands
### 3. Home Assistant Integration
The server maintains a robust connection to Home Assistant through:
- REST API calls
- WebSocket connections
- Event subscriptions
```typescript
interface HomeAssistantClient {
connect(): Promise<void>;
getState(entityId: string): Promise<EntityState>;
executeCommand(command: Command): Promise<CommandResult>;
subscribeToEvents(callback: EventCallback): Subscription;
}
```
### 4. AI Layer
#### Language Model Integration
- Processes natural language input
- Understands context and user intent
- Generates appropriate responses
#### Intent Classification
- Identifies command types
- Extracts parameters
- Validates requests
## Data Flow
1. Requests enter via the API endpoints.
2. Security middleware validates and processes requests.
3. Core modules process data and execute the necessary business logic.
4. Real-time notifications are managed by the SSE module.
### 1. Command Processing
## Future Enhancements
```mermaid
sequenceDiagram
participant Client
participant API
participant NLP
participant LLM
participant HA
- Expand modularity with potential microservices.
- Enhance security with multi-factor authentication.
- Improve scalability through distributed architectures.
Client->>API: Send command
API->>NLP: Process text
NLP->>LLM: Get intent
LLM-->>NLP: Return structured intent
NLP->>HA: Execute command
HA-->>API: Return result
API-->>Client: Send response
```
*Further diagrams and detailed breakdowns will be added in future updates.*
### 2. Real-time Updates
```mermaid
sequenceDiagram
participant HA
participant Cache
participant SSE
participant Client
HA->>Cache: State change
Cache->>SSE: Notify change
SSE->>Client: Send update
Note over Client: Update UI
```
### 3. [SSE API](api/sse.md)
- Event Subscriptions
- Real-time Updates
- Connection Management
## Security Architecture
### Authentication Flow
1. **JWT-based Authentication**
```typescript
interface AuthToken {
token: string;
expires: number;
scope: string[];
}
```
2. **Rate Limiting**
```typescript
interface RateLimit {
window: number;
max: number;
current: number;
}
```
### Security Measures
- TLS encryption for all communications
- Input sanitization
- Request validation
- Token-based authentication
- Rate limiting
- IP filtering
## Performance Optimizations
### Caching Strategy
```mermaid
graph LR
Request --> Cache{Cache?}
Cache -->|Hit| Response
Cache -->|Miss| HA[Home Assistant]
HA --> Cache
Cache --> Response
```
### Connection Management
- Connection pooling
- Automatic reconnection
- Load balancing
- Request queuing
## Configuration
The system is highly configurable through environment variables and configuration files:
```yaml
server:
port: 3000
host: '0.0.0.0'
homeAssistant:
url: 'http://homeassistant:8123'
token: 'YOUR_TOKEN'
security:
jwtSecret: 'your-secret'
rateLimit: 100
ai:
model: 'gpt-4'
temperature: 0.7
cache:
ttl: 300
maxSize: '100mb'
```
## Deployment Architecture
### Docker Deployment
```mermaid
graph TD
subgraph "Docker Compose"
MCP[MCP Server]
Redis[Redis Cache]
HA[Home Assistant]
end
MCP --> Redis
MCP --> HA
```
### Scaling Considerations
- Horizontal scaling capabilities
- Load balancing support
- Redis cluster support
- Multiple HA instance support
## Further Reading
- [API Documentation](api/index.md)
- [Installation Guide](getting-started/installation.md)
- [Contributing Guidelines](contributing.md)
- [Troubleshooting](troubleshooting.md)

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:root {
--md-primary-fg-color: #1a73e8;
--md-primary-fg-color--light: #5195ee;
--md-primary-fg-color--dark: #0d47a1;
}
.md-header {
box-shadow: 0 0 0.2rem rgba(0,0,0,.1), 0 0.2rem 0.4rem rgba(0,0,0,.2);
}
.md-main__inner {
margin-top: 1.5rem;
}
.md-typeset h1 {
font-weight: 700;
color: var(--md-primary-fg-color);
}
.md-typeset .admonition {
font-size: .8rem;
}
code {
background-color: rgba(175,184,193,0.2);
padding: .2em .4em;
border-radius: 6px;
}

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{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": [
"run",
"start",
"--port",
"8080"
],
"env": {
"NODE_ENV": "production"
}
}
}
}

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View File

@@ -0,0 +1,18 @@
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": [
"run",
"start",
"--enable-cline",
"--config",
"${configDir}/.env"
],
"env": {
"NODE_ENV": "production",
"CLINE_MODE": "true"
}
}
}
}

View File

@@ -1,36 +1,254 @@
# Contributing to Home Assistant MCP
---
layout: default
title: Contributing
nav_order: 5
---
We welcome community contributions to improve the MCP Server. Please review the following guidelines before contributing.
# Contributing Guide 🤝
## How to Contribute
Thank you for your interest in contributing to the MCP Server project! This guide will help you get started with contributing to the project.
1. **Fork the Repository:** Create your personal fork on GitHub.
2. **Create a Feature Branch:** Use a clear name (e.g., `feature/your-feature` or `bugfix/short-description`).
3. **Make Changes:** Develop your feature or fix bugs while following our coding standards.
4. **Write Tests:** Include tests for new features or bug fixes.
5. **Submit a Pull Request:** Once your changes are complete, submit a PR for review.
6. **Address Feedback:** Revise your PR based on maintainers' suggestions.
## Getting Started
## Code Style Guidelines
### Prerequisites
- Follow the project's established coding style.
- Use Bun tooling for linting and formatting:
- `bun run lint`
- `bun run format`
Before you begin, ensure you have:
- [Bun](https://bun.sh) >= 1.0.26
- [Node.js](https://nodejs.org) >= 18
- [Docker](https://www.docker.com) (optional, for containerized development)
- A running Home Assistant instance for testing
### Development Setup
1. Fork and clone the repository:
```bash
git clone https://github.com/YOUR_USERNAME/advanced-homeassistant-mcp.git
cd advanced-homeassistant-mcp
```
2. Install dependencies:
```bash
bun install
```
3. Set up your development environment:
```bash
cp .env.example .env
# Edit .env with your Home Assistant details
```
4. Start the development server:
```bash
bun run dev
```
## Development Workflow
### Branch Naming Convention
- `feature/` - New features
- `fix/` - Bug fixes
- `docs/` - Documentation updates
- `refactor/` - Code refactoring
- `test/` - Test improvements
Example:
```bash
git checkout -b feature/voice-commands
```
### Commit Messages
We follow the [Conventional Commits](https://www.conventionalcommits.org/) specification:
```
type(scope): description
[optional body]
[optional footer]
```
Types:
- `feat:` - New features
- `fix:` - Bug fixes
- `docs:` - Documentation changes
- `style:` - Code style changes (formatting, etc.)
- `refactor:` - Code refactoring
- `test:` - Test updates
- `chore:` - Maintenance tasks
Examples:
```bash
feat(api): add voice command endpoint
fix(sse): resolve connection timeout issue
docs(readme): update installation instructions
```
### Testing
Run tests before submitting your changes:
```bash
# Run all tests
bun test
# Run specific test file
bun test test/api/command.test.ts
# Run tests with coverage
bun test --coverage
```
### Code Style
We use ESLint and Prettier for code formatting:
```bash
# Check code style
bun run lint
# Fix code style issues
bun run lint:fix
```
## Pull Request Process
1. **Update Documentation**
- Add/update relevant documentation
- Include inline code comments where necessary
- Update API documentation if endpoints change
2. **Write Tests**
- Add tests for new features
- Update existing tests if needed
- Ensure all tests pass
3. **Create Pull Request**
- Fill out the PR template
- Link related issues
- Provide clear description of changes
4. **Code Review**
- Address review comments
- Keep discussions focused
- Be patient and respectful
### PR Template
```markdown
## Description
Brief description of the changes
## Type of Change
- [ ] Bug fix
- [ ] New feature
- [ ] Breaking change
- [ ] Documentation update
## How Has This Been Tested?
Describe your test process
## Checklist
- [ ] Tests added/updated
- [ ] Documentation updated
- [ ] Code follows style guidelines
- [ ] All tests passing
```
## Development Guidelines
### Code Organization
```
src/
├── api/ # API endpoints
├── core/ # Core functionality
├── models/ # Data models
├── services/ # Business logic
├── utils/ # Utility functions
└── types/ # TypeScript types
```
### Best Practices
1. **Type Safety**
```typescript
// Use explicit types
interface CommandRequest {
command: string;
parameters?: Record<string, unknown>;
}
function processCommand(request: CommandRequest): Promise<CommandResponse> {
// Implementation
}
```
2. **Error Handling**
```typescript
try {
await processCommand(request);
} catch (error) {
if (error instanceof ValidationError) {
// Handle validation errors
}
throw error;
}
```
3. **Async/Await**
```typescript
// Prefer async/await over promises
async function handleRequest() {
const result = await processData();
return result;
}
```
## Documentation
- Update documentation alongside your code changes.
- Ensure tests pass and coverage remains high.
### API Documentation
## Reporting Issues
Update API documentation when adding/modifying endpoints:
- Use the GitHub Issues page to report bugs, request new features, or ask questions.
- Provide clear descriptions, replication steps, and any error logs.
```typescript
/**
* Process a voice command
* @param command - The voice command to process
* @returns Promise<CommandResult>
* @throws {ValidationError} If command is invalid
*/
async function processVoiceCommand(command: string): Promise<CommandResult> {
// Implementation
}
```
## Community
### README Updates
- Join our real-time discussions on our chat platforms (Discord, Slack, etc.).
- Engage with other contributors to exchange ideas and solutions.
Keep the README up to date with:
- New features
- Changed requirements
- Updated examples
- Modified configuration
Thank you for helping improve the Home Assistant MCP project!
## Getting Help
- Check [Discussions](https://github.com/jango-blockchained/advanced-homeassistant-mcp/discussions)
- Review existing [Issues](https://github.com/jango-blockchained/advanced-homeassistant-mcp/issues)
## Community Guidelines
We expect all contributors to:
- Be respectful and inclusive
- Focus on constructive feedback
- Help maintain a positive environment
- Follow our code style guidelines
- Write clear documentation
- Test their code thoroughly
## License
By contributing, you agree that your contributions will be licensed under the MIT License.

View File

@@ -4,7 +4,7 @@ Begin your journey with the Home Assistant MCP Server by following these steps:
- **API Documentation:** Read the [API Documentation](api.md) for available endpoints.
- **Real-Time Updates:** Learn about [Server-Sent Events](sse-api.md) for live communication.
- **Tools:** Explore available [Tools](tools/README.md) for device control and automation.
- **Tools:** Explore available [Tools](tools/tools.md) for device control and automation.
- **Configuration:** Refer to the [Configuration Guide](configuration.md) for setup and advanced settings.
## Troubleshooting
@@ -19,7 +19,7 @@ If you encounter any issues:
For contributors:
1. Fork the repository.
2. Create a feature branch.
3. Follow the [Development Guide](development/README.md) for contribution guidelines.
3. Follow the [Development Guide](development/development.md) for contribution guidelines.
4. Submit a pull request with your enhancements.
## Support

View File

@@ -1,124 +1,171 @@
# Installation Guide
---
layout: default
title: Installation
parent: Getting Started
nav_order: 1
---
# Installation Guide 🛠️
This guide covers different methods to install and set up the MCP Server for Home Assistant. Choose the installation method that best suits your needs.
## Prerequisites
### System Requirements
- **Operating System:** Linux, macOS, or Windows (Docker recommended)
- **Runtime:** Bun v1.0.26 or higher
- **Home Assistant:** v2023.11 or higher
- **Minimum Hardware:**
- 2 CPU cores
- 2GB RAM
- 10GB free disk space
Before installing MCP Server, ensure you have:
### Software Dependencies
- Bun runtime
- Docker (optional, recommended for deployment)
- Git
- Node.js (for some development tasks)
- Home Assistant instance running and accessible
- Node.js 18+ or Docker installed
- Home Assistant Long-Lived Access Token ([How to get one](https://developers.home-assistant.io/docs/auth_api/#long-lived-access-token))
## Installation Methods
### 1. Basic Setup
### 1. 🔧 Smithery Installation (Recommended)
The easiest way to install MCP Server is through Smithery:
#### Install Bun
```bash
curl -fsSL https://bun.sh/install | bash
npx -y @smithery/cli install @jango-blockchained/advanced-homeassistant-mcp --client claude
```
#### Clone Repository
```bash
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
```
### 2. 🐳 Docker Installation
#### Install Dependencies
```bash
bun install
```
For a containerized deployment:
#### Configure Environment
1. Copy environment template
```bash
# Clone the repository
git clone --depth 1 https://github.com/jango-blockchained/advanced-homeassistant-mcp.git
cd advanced-homeassistant-mcp
# Configure environment variables
cp .env.example .env
```
2. Edit `.env` file with your Home Assistant configuration
- Set `HASS_HOST`
- Configure authentication tokens
- Adjust other settings as needed
# Edit .env with your Home Assistant details:
# - HA_URL: Your Home Assistant URL
# - HA_TOKEN: Your Long-Lived Access Token
# - Other configuration options
#### Build and Start
```bash
bun run build
bun start
# Build and start containers
docker compose up -d --build
# View logs (optional)
docker compose logs -f --tail=50
```
### 2. Docker Setup (Recommended)
### 3. 💻 Manual Installation
#### Prerequisites
- Docker
- Docker Compose
For direct installation on your system:
#### Deployment Steps
```bash
# Clone repository
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
# Install Bun runtime
curl -fsSL https://bun.sh/install | bash
# Clone and install
git clone https://github.com/jango-blockchained/advanced-homeassistant-mcp.git
cd advanced-homeassistant-mcp
bun install --frozen-lockfile
# Configure environment
cp .env.example .env
# Edit .env file with your settings
# Edit .env with your configuration
# Deploy with Docker Compose
docker compose up -d
# Start the server
bun run dev --watch
```
### 3. Home Assistant Add-on (Coming Soon)
We're working on a direct Home Assistant add-on for even easier installation.
## Configuration
### Environment Variables
Key configuration options in your `.env` file:
```env
# Home Assistant Configuration
HA_URL=http://your-homeassistant:8123
HA_TOKEN=your_long_lived_access_token
# Server Configuration
PORT=3000
HOST=0.0.0.0
NODE_ENV=production
# Security Settings
JWT_SECRET=your_secure_jwt_secret
RATE_LIMIT=100
```
### Client Integration
#### Cursor Integration
Add to `.cursor/config/config.json`:
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": ["run", "start"],
"cwd": "${workspaceRoot}",
"env": {
"NODE_ENV": "development"
}
}
}
}
```
#### Claude Desktop Integration
Add to your Claude configuration:
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": ["run", "start", "--port", "8080"],
"env": {
"NODE_ENV": "production"
}
}
}
}
```
## Verification
### Check Installation
- Web Interface: [http://localhost:3000](http://localhost:3000)
- Logs: `docker compose logs` or check `logs/` directory
To verify your installation:
### Troubleshooting
- Ensure all environment variables are correctly set
- Check network connectivity to Home Assistant
- Verify authentication tokens
## Updating
### Basic Setup
1. Check server status:
```bash
git pull
bun install
bun run build
bun start
curl http://localhost:3000/health
```
### Docker
2. Test Home Assistant connection:
```bash
git pull
docker compose up -d --build
curl http://localhost:3000/api/state
```
## Uninstallation
## Troubleshooting
### Basic Setup
```bash
cd homeassistant-mcp
bun stop # Stop the application
rm -rf node_modules dist
```
If you encounter issues:
### Docker
1. Check the [Troubleshooting Guide](../troubleshooting.md)
2. Verify your environment variables
3. Check server logs:
```bash
docker compose down
docker rmi homeassistant-mcp # Remove image
# For Docker installation
docker compose logs -f
# For manual installation
bun run dev
```
## Next Steps
- [Configuration Guide](configuration.md)
- [Usage Instructions](../usage.md)
- [Troubleshooting](../troubleshooting.md)
- Follow the [Quick Start Guide](quickstart.md) to begin using MCP Server
- Read the [API Documentation](../api/index.md) for integration details
- Check the [Architecture Overview](../architecture.md) to understand the system
## Support
Need help? Check our [Support Resources](../index.md#support) or [open an issue](https://github.com/jango-blockchained/advanced-homeassistant-mcp/issues).

View File

@@ -0,0 +1,219 @@
---
layout: default
title: Quick Start
parent: Getting Started
nav_order: 2
---
# Quick Start Guide 🚀
This guide will help you get started with MCP Server after installation. We'll cover basic usage, common commands, and simple integrations.
## First Steps
### 1. Verify Connection
After installation, verify your MCP Server is running and connected to Home Assistant:
```bash
# Check server health
curl http://localhost:3000/health
# Verify Home Assistant connection
curl http://localhost:3000/api/state
```
### 2. Basic Voice Commands
Try these basic voice commands to test your setup:
```bash
# Example using curl for testing
curl -X POST http://localhost:3000/api/command \
-H "Content-Type: application/json" \
-d '{"command": "Turn on the living room lights"}'
```
Common voice commands:
- "Turn on/off [device name]"
- "Set [device] to [value]"
- "What's the temperature in [room]?"
- "Is [device] on or off?"
## Real-World Examples
### 1. Smart Lighting Control
```javascript
// Browser example using fetch
const response = await fetch('http://localhost:3000/api/command', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
command: 'Set living room lights to 50% brightness and warm white color'
})
});
```
### 2. Real-Time Updates
Subscribe to device state changes using Server-Sent Events (SSE):
```javascript
const eventSource = new EventSource('http://localhost:3000/subscribe_events?token=YOUR_TOKEN&domain=light');
eventSource.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('Device state changed:', data);
// Update your UI here
};
```
### 3. Scene Automation
Create and trigger scenes for different activities:
```javascript
// Create a "Movie Night" scene
const createScene = async () => {
await fetch('http://localhost:3000/api/scene', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
name: 'Movie Night',
actions: [
{ device: 'living_room_lights', action: 'dim', value: 20 },
{ device: 'tv', action: 'on' },
{ device: 'soundbar', action: 'on' }
]
})
});
};
// Trigger the scene with voice command:
// "Hey MCP, activate movie night scene"
```
## Integration Examples
### 1. Web Dashboard Integration
```javascript
// React component example
function SmartHomeControl() {
const [devices, setDevices] = useState([]);
useEffect(() => {
// Subscribe to device updates
const events = new EventSource('http://localhost:3000/subscribe_events');
events.onmessage = (event) => {
const data = JSON.parse(event.data);
setDevices(currentDevices =>
currentDevices.map(device =>
device.id === data.id ? {...device, ...data} : device
)
);
};
return () => events.close();
}, []);
return (
<div className="dashboard">
{devices.map(device => (
<DeviceCard key={device.id} device={device} />
))}
</div>
);
}
```
### 2. Voice Assistant Integration
```typescript
// Example using speech-to-text with MCP
async function handleVoiceCommand(audioBlob: Blob) {
// First, convert speech to text
const text = await speechToText(audioBlob);
// Then send command to MCP
const response = await fetch('http://localhost:3000/api/command', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ command: text })
});
return response.json();
}
```
## Best Practices
1. **Error Handling**
```javascript
try {
const response = await fetch('http://localhost:3000/api/command', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ command: 'Turn on lights' })
});
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
const data = await response.json();
} catch (error) {
console.error('Error:', error);
// Handle error appropriately
}
```
2. **Connection Management**
```javascript
class MCPConnection {
constructor() {
this.eventSource = null;
this.reconnectAttempts = 0;
}
connect() {
this.eventSource = new EventSource('http://localhost:3000/subscribe_events');
this.eventSource.onerror = this.handleError.bind(this);
}
handleError() {
if (this.reconnectAttempts < 3) {
setTimeout(() => {
this.reconnectAttempts++;
this.connect();
}, 1000 * this.reconnectAttempts);
}
}
}
```
## Next Steps
- Explore the [API Documentation](../api/index.md) for advanced features
- Learn about [SSE API](../api/sse.md) for real-time updates
- Check out [Architecture](../architecture.md) for system design details
- Read the [Contributing Guide](../contributing.md) to get involved
## Troubleshooting
If you encounter issues:
- Verify your authentication token
- Check server logs for errors
- Ensure Home Assistant is accessible
- Review the [Troubleshooting Guide](../troubleshooting.md)
Need more help? Visit our [Support Resources](../index.md#support).

View File

@@ -4,84 +4,52 @@ title: Home
nav_order: 1
---
# Model Context Protocol (MCP) Server
# 🚀 MCP Server for Home Assistant
## Overview
Welcome to the Model Context Protocol (MCP) Server documentation! This guide will help you get started with integrating AI-powered natural language processing into your Home Assistant setup.
The Model Context Protocol (MCP) Server is a cutting-edge bridge between Home Assistant and Language Learning Models (LLMs), designed to revolutionize smart home automation and control. This documentation provides comprehensive information about setting up, configuring, and using the Home Assistant MCP.
## What is MCP Server?
MCP Server is a bridge between Home Assistant and Language Learning Models (LLMs), enabling natural language interactions and real-time automation of your smart devices. It allows you to control your home automation setup using natural language commands while maintaining high performance and security.
## Key Features
### 🏠 Smart Home Integration
- Natural language control of smart devices
- Real-time device state monitoring
- Advanced automation capabilities
### 🎮 Device Control & Monitoring
- Voice-controlled automation
- Real-time updates via SSE/WebSocket
- Scene-based automation rules
### 🤖 LLM Powered Interactions
- Intuitive voice and text-based commands
- Context-aware device management
- Intelligent automation suggestions
### 🤖 AI-Powered Features
- Natural Language Processing (NLP)
- Predictive automation
- Anomaly detection
### 🔒 Security & Performance
- Token-based authentication
- High-performance Bun runtime
- Secure, real-time communication protocols
### 🛡️ Security & Performance
- JWT authentication
- Request sanitization
- Sub-100ms latency
- Rate limiting
## Documentation
## Documentation Structure
### Getting Started
- [Installation Guide](getting-started/installation.md) - Set up MCP Server
- [Quick Start Tutorial](getting-started/quickstart.md) - Basic usage examples
### Core Documentation
1. [Getting Started](getting-started.md)
- Installation and basic setup
- Configuration
- First Steps
- [API Documentation](api/index.md) - Complete API reference
- [Architecture Overview](architecture.md) - System design and components
- [Contributing Guidelines](contributing.md) - How to contribute
- [Troubleshooting Guide](troubleshooting.md) - Common issues and solutions
2. [API Reference](api.md)
- REST API Endpoints
- Authentication
- Error Handling
## Support
3. [SSE API](sse-api.md)
- Event Subscriptions
- Real-time Updates
- Connection Management
If you need help or want to report issues:
### Advanced Topics
4. [Architecture](architecture.md)
- System Design
- Components
- Data Flow
5. [Configuration](getting-started.md#configuration)
- Environment Variables
- Security Settings
- Performance Tuning
6. [Development Guide](development/README.md)
- Project Structure
- Contributing Guidelines
- Testing
7. [Troubleshooting](troubleshooting.md)
- Common Issues
- Debugging
- FAQ
## Quick Links
- [GitHub Repository](https://github.com/jango-blockchained/homeassistant-mcp)
- [Issue Tracker](https://github.com/jango-blockchained/homeassistant-mcp/issues)
- [Contributing Guide](contributing.md)
- [Roadmap](roadmap.md)
## Community and Support
If you need help or have questions:
1. Check the [Troubleshooting Guide](troubleshooting.md)
2. Search existing [Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues)
3. Join our [GitHub Discussions](https://github.com/jango-blockchained/homeassistant-mcp/discussions)
4. Create a new issue if your problem isn't already reported
- [GitHub Issues](https://github.com/jango-blockchained/advanced-homeassistant-mcp/issues)
- [GitHub Discussions](https://github.com/jango-blockchained/advanced-homeassistant-mcp/discussions)
- [Contributing Guidelines](contributing.md)
## License
This project is licensed under the MIT License. See [LICENSE](https://github.com/jango-blockchained/homeassistant-mcp/blob/main/LICENSE) for details.
This project is licensed under the MIT License. See the [LICENSE](https://github.com/jango-blockchained/advanced-homeassistant-mcp/blob/main/LICENSE) file for details.

View File

@@ -1,345 +1,315 @@
# Troubleshooting Guide
---
layout: default
title: Troubleshooting
nav_order: 6
---
This guide provides solutions to common issues encountered with the Home Assistant MCP Server.
# Troubleshooting Guide 🔧
This guide helps you diagnose and resolve common issues with MCP Server.
## Quick Diagnostics
### Health Check
First, verify the server's health:
```bash
curl http://localhost:3000/health
```
Expected response:
```json
{
"status": "healthy",
"version": "1.0.0",
"uptime": 3600,
"homeAssistant": {
"connected": true,
"version": "2024.1.0"
}
}
```
## Common Issues
- **Server Not Starting:**
- Verify that all required environment variables are correctly set.
- Check for port conflicts or missing dependencies.
- Review the server logs for error details.
### 1. Connection Issues
- **Connection Problems:**
- Ensure your Home Assistant instance is reachable.
- Confirm that the authentication token is valid.
- Check network configurations and firewalls.
## Tool Issues
### Tool Not Found
#### Cannot Connect to MCP Server
**Symptoms:**
- "Tool not found" errors or 404 responses.
- Server not responding
- Connection refused errors
- Timeout errors
**Solutions:**
- Double-check the tool name spelling.
- Verify that the tool is correctly registered.
- Review tool imports and documentation.
### Tool Execution Failures
1. Check if the server is running:
```bash
# For Docker installation
docker compose ps
# For manual installation
ps aux | grep mcp
```
2. Verify port availability:
```bash
# Check if port is in use
netstat -tuln | grep 3000
```
3. Check logs:
```bash
# Docker logs
docker compose logs mcp
# Manual installation logs
bun run dev
```
#### Home Assistant Connection Failed
**Symptoms:**
- Execution errors or timeouts.
- "Connection Error" in health check
- Cannot control devices
- State updates not working
**Solutions:**
- Validate input parameters.
- Check and review error logs.
- Debug the tool implementation.
- Ensure proper permissions in Home Assistant.
## Debugging Steps
1. Verify Home Assistant URL and token in `.env`:
```env
HA_URL=http://homeassistant:8123
HA_TOKEN=your_long_lived_access_token
```
### Server Logs
2. Test Home Assistant connection:
```bash
curl -H "Authorization: Bearer YOUR_HA_TOKEN" \
http://your-homeassistant:8123/api/
```
3. Check network connectivity:
```bash
# For Docker setup
docker compose exec mcp ping homeassistant
```
### 2. Authentication Issues
#### Invalid Token
**Symptoms:**
- 401 Unauthorized responses
- "Invalid token" errors
**Solutions:**
1. Generate a new token:
```bash
curl -X POST http://localhost:3000/auth/token \
-H "Content-Type: application/json" \
-d '{"username": "your_username", "password": "your_password"}'
```
2. Verify token format:
```javascript
// Token should be in format:
Authorization: Bearer eyJhbGciOiJIUzI1NiIs...
```
#### Rate Limiting
**Symptoms:**
- 429 Too Many Requests
- "Rate limit exceeded" errors
**Solutions:**
1. Check current rate limit status:
```bash
curl -I http://localhost:3000/api/state
```
2. Adjust rate limits in configuration:
```yaml
security:
rateLimit: 100 # Increase if needed
rateLimitWindow: 60000 # Window in milliseconds
```
### 3. Real-time Updates Issues
#### SSE Connection Drops
**Symptoms:**
- Frequent disconnections
- Missing state updates
- EventSource errors
**Solutions:**
1. Implement proper reconnection logic:
```javascript
class SSEClient {
constructor() {
this.connect();
}
connect() {
this.eventSource = new EventSource('/subscribe_events');
this.eventSource.onerror = this.handleError.bind(this);
}
handleError(error) {
console.error('SSE Error:', error);
this.eventSource.close();
setTimeout(() => this.connect(), 1000);
}
}
```
2. Check network stability:
```bash
# Monitor connection stability
ping -c 100 localhost
```
### 4. Performance Issues
#### High Latency
**Symptoms:**
- Slow response times
- Command execution delays
- UI lag
**Solutions:**
1. Enable Redis caching:
```env
REDIS_ENABLED=true
REDIS_URL=redis://localhost:6379
```
2. Monitor system resources:
```bash
# Check CPU and memory usage
docker stats
# Or for manual installation
top -p $(pgrep -f mcp)
```
3. Optimize database queries and caching:
```typescript
// Use batch operations
const results = await Promise.all([
cache.get('key1'),
cache.get('key2')
]);
```
### 5. Device Control Issues
#### Commands Not Executing
**Symptoms:**
- Commands appear successful but no device response
- Inconsistent device states
- Error messages from Home Assistant
**Solutions:**
1. Verify device availability:
```bash
curl http://localhost:3000/api/state/light.living_room
```
2. Check command syntax:
```bash
# Test basic command
curl -X POST http://localhost:3000/api/command \
-H "Content-Type: application/json" \
-d '{"command": "Turn on living room lights"}'
```
3. Review Home Assistant logs:
```bash
docker compose exec homeassistant journalctl -f
```
## Debugging Tools
### Log Analysis
Enable debug logging:
1. Enable debug logging by setting:
```env
LOG_LEVEL=debug
```
2. Check logs:
```bash
npm run logs
```
3. Filter errors:
```bash
npm run logs | grep "error"
DEBUG=mcp:*
```
### Network Debugging
1. Test API endpoints:
Monitor network traffic:
```bash
curl -v http://localhost:3000/api/health
```
2. Monitor SSE connections:
```bash
curl -N http://localhost:3000/api/sse/stats
```
3. Test WebSocket connectivity:
```bash
wscat -c ws://localhost:3000
# TCP dump for API traffic
tcpdump -i any port 3000 -w debug.pcap
```
### Performance Issues
### Performance Profiling
- Monitor memory usage with:
```bash
npm run stats
Enable performance monitoring:
```env
ENABLE_METRICS=true
METRICS_PORT=9090
```
## Security Middleware Troubleshooting
### Rate Limiting Problems
**Symptoms:** Receiving 429 (Too Many Requests) errors.
**Solutions:**
- Adjust and fine-tune rate limit settings.
- Consider different limits for critical versus non-critical endpoints.
### Request Validation Failures
**Symptoms:** 400 or 415 errors on valid requests.
**Solutions:**
- Verify that the `Content-Type` header is set correctly.
- Inspect request payload size and format.
### Input Sanitization Issues
**Symptoms:** Unexpected data transformation or loss.
**Solutions:**
- Test sanitization with various input types.
- Implement custom sanitization for complex data if needed.
### Security Header Configuration
**Symptoms:** Missing or improper security headers.
**Solutions:**
- Review and update security header configurations (e.g., Helmet settings).
- Ensure environment-specific header settings are in place.
### Error Handling and Logging
**Symptoms:** Inconsistent error responses.
**Solutions:**
- Enhance logging for detailed error tracking.
- Adjust error handlers for production and development differences.
## Additional Resources
- [OWASP Security Guidelines](https://owasp.org/www-project-top-ten/)
- [Helmet.js Documentation](https://helmetjs.github.io/)
- [JWT Security Best Practices](https://jwt.io/introduction)
## Getting Help
If issues persist:
1. Review detailed logs.
2. Verify your configuration and environment.
3. Consult the GitHub issue tracker or community forums.
If you're still experiencing issues:
## FAQ
### Q: How do I reset my configuration?
A: Delete `.env` and copy `.env.example` to start fresh.
### Q: Why are my events delayed?
A: Check network latency and server load. Consider adjusting buffer sizes.
### Q: How do I update my token?
A: Generate a new token in Home Assistant and update HASS_TOKEN.
### Q: Why do I get "Maximum clients reached"?
A: Adjust SSE_MAX_CLIENTS in configuration or clean up stale connections.
## Error Codes
- `E001`: Connection Error
- `E002`: Authentication Error
- `E003`: Rate Limit Error
- `E004`: Tool Error
- `E005`: Configuration Error
## Support Resources
1. Documentation
- [API Reference](./API.md)
- [Configuration Guide](./configuration/README.md)
- [Development Guide](./development/README.md)
2. Community
- GitHub Issues
- Discussion Forums
- Stack Overflow
3. Tools
- Diagnostic Scripts
- Testing Tools
- Monitoring Tools
## Still Need Help?
1. Create a detailed issue:
- Error messages
- Steps to reproduce
- Environment details
1. Check the [GitHub Issues](https://github.com/jango-blockchained/advanced-homeassistant-mcp/issues)
2. Search [Discussions](https://github.com/jango-blockchained/advanced-homeassistant-mcp/discussions)
3. Create a new issue with:
- Detailed description
- Logs
- Configuration (sanitized)
- Steps to reproduce
2. Contact support:
- GitHub Issues
- Email Support
- Community Forums
## Maintenance
## Security Middleware Troubleshooting
### Regular Health Checks
### Common Issues and Solutions
Run periodic health checks:
#### Rate Limiting Problems
**Symptom**: Unexpected 429 (Too Many Requests) errors
**Possible Causes**:
- Misconfigured rate limit settings
- Shared IP addresses (e.g., behind NAT)
- Aggressive client-side retry mechanisms
**Solutions**:
1. Adjust rate limit parameters
```typescript
// Customize rate limit for specific scenarios
checkRateLimit(ip, maxRequests = 200, windowMs = 30 * 60 * 1000)
```bash
# Create a cron job
*/5 * * * * curl -f http://localhost:3000/health || notify-admin
```
2. Implement more granular rate limiting
- Use different limits for different endpoints
- Consider user authentication level
### Log Rotation
#### Request Validation Failures
Configure log rotation:
**Symptom**: 400 or 415 status codes on valid requests
**Possible Causes**:
- Incorrect `Content-Type` header
- Large request payloads
- Malformed authorization headers
**Debugging Steps**:
1. Verify request headers
```typescript
// Check content type and size
validateRequestHeaders(request, 'application/json')
```yaml
logging:
maxSize: "100m"
maxFiles: "7d"
compress: true
```
2. Log detailed validation errors
```typescript
try {
validateRequestHeaders(request);
} catch (error) {
console.error('Request validation failed:', error.message);
}
### Backup Configuration
Regularly backup your configuration:
```bash
# Backup script
tar -czf mcp-backup-$(date +%Y%m%d).tar.gz \
.env \
config/ \
data/
```
#### Input Sanitization Issues
**Symptom**: Unexpected data transformation or loss
**Possible Causes**:
- Complex nested objects
- Non-standard input formats
- Overly aggressive sanitization
**Troubleshooting**:
1. Test sanitization with various input types
```typescript
const input = {
text: '<script>alert("xss")</script>',
nested: { html: '<img src="x" onerror="alert(1)">World' }
};
const sanitized = sanitizeValue(input);
```
2. Custom sanitization for specific use cases
```typescript
function customSanitize(value) {
// Add custom sanitization logic
return sanitizeValue(value);
}
```
#### Security Header Configuration
**Symptom**: Missing or incorrect security headers
**Possible Causes**:
- Misconfigured Helmet options
- Environment-specific header requirements
**Solutions**:
1. Custom security header configuration
```typescript
const customHelmetConfig = {
contentSecurityPolicy: {
directives: {
defaultSrc: ["'self'"],
scriptSrc: ["'self'", 'trusted-cdn.com']
}
}
};
applySecurityHeaders(request, customHelmetConfig);
```
#### Error Handling and Logging
**Symptom**: Inconsistent error responses
**Possible Causes**:
- Incorrect environment configuration
- Unhandled error types
**Debugging Techniques**:
1. Verify environment settings
```typescript
const errorResponse = handleError(error, process.env.NODE_ENV);
```
2. Add custom error handling
```typescript
function enhancedErrorHandler(error, env) {
// Add custom logging or monitoring
console.error('Security error:', error);
return handleError(error, env);
}
```
### Performance and Security Monitoring
1. **Logging**
- Enable debug logging for security events
- Monitor rate limit and validation logs
2. **Metrics**
- Track rate limit hit rates
- Monitor request validation success/failure ratios
3. **Continuous Improvement**
- Regularly review and update security configurations
- Conduct periodic security audits
### Environment-Specific Considerations
#### Development
- More verbose error messages
- Relaxed rate limiting
- Detailed security logs
#### Production
- Minimal error details
- Strict rate limiting
- Comprehensive security headers
### External Resources
- [OWASP Security Guidelines](https://owasp.org/www-project-top-ten/)
- [Helmet.js Documentation](https://helmetjs.github.io/)
- [JWT Security Best Practices](https://jwt.io/introduction)
### Getting Help
If you encounter persistent issues:
1. Check application logs
2. Verify environment configurations
3. Consult the project's issue tracker
4. Reach out to the development team with detailed error information

View File

@@ -21,13 +21,13 @@ This guide explains how to use the Home Assistant MCP Server for smart home devi
- See [API Documentation](api.md) for details.
2. **Tool Integrations:**
- Multiple tools are available (see [Tools Documentation](tools/README.md)), for tasks like automation management and notifications.
- Multiple tools are available (see [Tools Documentation](tools/tools.md)), for tasks like automation management and notifications.
3. **Security Settings:**
- Configure token-based authentication and environment variables as per the [Configuration Guide](getting-started/configuration.md).
4. **Customization and Extensions:**
- Extend server functionality by developing new tools as outlined in the [Development Guide](development/README.md).
- Extend server functionality by developing new tools as outlined in the [Development Guide](development/development.md).
## Troubleshooting

91
examples/README.md Normal file
View File

@@ -0,0 +1,91 @@
# Speech-to-Text Examples
This directory contains examples demonstrating how to use the speech-to-text integration with wake word detection.
## Prerequisites
1. Make sure you have Docker installed and running
2. Build and start the services:
```bash
docker-compose up -d
```
## Running the Example
1. Install dependencies:
```bash
npm install
```
2. Run the example:
```bash
npm run example:speech
```
Or using `ts-node` directly:
```bash
npx ts-node examples/speech-to-text-example.ts
```
## Features Demonstrated
1. **Wake Word Detection**
- Listens for wake words: "hey jarvis", "ok google", "alexa"
- Automatically saves audio when wake word is detected
- Transcribes the detected speech
2. **Manual Transcription**
- Example of how to transcribe audio files manually
- Supports different models and configurations
3. **Event Handling**
- Wake word detection events
- Transcription results
- Progress updates
- Error handling
## Example Output
When a wake word is detected, you'll see output like this:
```
🎤 Wake word detected!
Timestamp: 20240203_123456
Audio file: /path/to/audio/wake_word_20240203_123456.wav
Metadata file: /path/to/audio/wake_word_20240203_123456.wav.json
📝 Transcription result:
Full text: This is what was said after the wake word.
Segments:
1. [0.00s - 1.52s] (95.5% confidence)
"This is what was said"
2. [1.52s - 2.34s] (98.2% confidence)
"after the wake word."
```
## Customization
You can customize the behavior by:
1. Changing the wake word models in `docker/speech/Dockerfile`
2. Modifying transcription options in the example file
3. Adding your own event handlers
4. Implementing different audio processing logic
## Troubleshooting
1. **Docker Issues**
- Make sure Docker is running
- Check container logs: `docker-compose logs fast-whisper`
- Verify container is up: `docker ps`
2. **Audio Issues**
- Check audio device permissions
- Verify audio file format (WAV files recommended)
- Check audio file permissions
3. **Performance Issues**
- Try using a smaller model (tiny.en or base.en)
- Adjust beam size and patience parameters
- Consider using GPU acceleration if available

View File

@@ -0,0 +1,91 @@
import { SpeechToText, TranscriptionResult, WakeWordEvent } from '../src/speech/speechToText';
import path from 'path';
async function main() {
// Initialize the speech-to-text service
const speech = new SpeechToText('fast-whisper');
// Check if the service is available
const isHealthy = await speech.checkHealth();
if (!isHealthy) {
console.error('Speech service is not available. Make sure Docker is running and the fast-whisper container is up.');
console.error('Run: docker-compose up -d');
process.exit(1);
}
console.log('Speech service is ready!');
console.log('Listening for wake words: "hey jarvis", "ok google", "alexa"');
console.log('Press Ctrl+C to exit');
// Set up event handlers
speech.on('wake_word', (event: WakeWordEvent) => {
console.log('\n🎤 Wake word detected!');
console.log(' Timestamp:', event.timestamp);
console.log(' Audio file:', event.audioFile);
console.log(' Metadata file:', event.metadataFile);
});
speech.on('transcription', (event: { audioFile: string; result: TranscriptionResult }) => {
console.log('\n📝 Transcription result:');
console.log(' Full text:', event.result.text);
console.log('\n Segments:');
event.result.segments.forEach((segment, index) => {
console.log(` ${index + 1}. [${segment.start.toFixed(2)}s - ${segment.end.toFixed(2)}s] (${(segment.confidence * 100).toFixed(1)}% confidence)`);
console.log(` "${segment.text}"`);
});
});
speech.on('progress', (event: { type: string; data: string }) => {
if (event.type === 'stderr' && !event.data.includes('Loading model')) {
console.error('❌ Error:', event.data);
}
});
speech.on('error', (error: Error) => {
console.error('❌ Error:', error.message);
});
// Example of manual transcription
async function transcribeFile(filepath: string) {
try {
console.log(`\n🎯 Manually transcribing: ${filepath}`);
const result = await speech.transcribeAudio(filepath, {
model: 'base.en', // You can change this to tiny.en, small.en, medium.en, or large-v2
language: 'en',
temperature: 0,
beamSize: 5
});
console.log('\n📝 Transcription result:');
console.log(' Text:', result.text);
} catch (error) {
console.error('❌ Transcription failed:', error instanceof Error ? error.message : error);
}
}
// Create audio directory if it doesn't exist
const audioDir = path.join(__dirname, '..', 'audio');
if (!require('fs').existsSync(audioDir)) {
require('fs').mkdirSync(audioDir, { recursive: true });
}
// Start wake word detection
speech.startWakeWordDetection(audioDir);
// Example: You can also manually transcribe files
// Uncomment the following line and replace with your audio file:
// await transcribeFile('/path/to/your/audio.wav');
// Keep the process running
process.on('SIGINT', () => {
console.log('\nStopping speech service...');
speech.stopWakeWordDetection();
process.exit(0);
});
}
// Run the example
main().catch(error => {
console.error('Fatal error:', error);
process.exit(1);
});

View File

@@ -327,3 +327,7 @@ if [[ $REPLY =~ ^[Yy]$ ]]; then
echo -e "${GREEN}Home Assistant MCP test successful!${NC}"
fi
fi
# macOS environment configuration
HASS_SOCKET_URL="${HASS_HOST/http/ws}/api/websocket" # WebSocket URL conversion
chmod 600 "$CLAUDE_CONFIG_DIR/claude_desktop_config.json" # Security hardening

View File

@@ -1,26 +1,108 @@
site_name: Home Assistant Model Context Protocol (MCP)
site_url: https://yourusername.github.io/your-repo-name/
repo_url: https://github.com/yourusername/your-repo-name
site_name: Home Assistant MCP
site_description: A bridge between Home Assistant and Language Learning Models
site_url: https://jango-blockchained.github.io/advanced-homeassistant-mcp/
repo_url: https://github.com/jango-blockchained/advanced-homeassistant-mcp
repo_name: jango-blockchained/advanced-homeassistant-mcp
theme:
name: material
logo: assets/images/logo.png
favicon: assets/images/favicon.ico
palette:
- media: "(prefers-color-scheme: light)"
scheme: default
primary: indigo
accent: indigo
toggle:
icon: material/brightness-7
name: Switch to dark mode
- media: "(prefers-color-scheme: dark)"
scheme: slate
primary: indigo
accent: indigo
toggle:
icon: material/brightness-4
name: Switch to light mode
features:
- navigation.tabs
- navigation.instant
- navigation.tracking
- navigation.sections
- toc.integrate
- navigation.expand
- navigation.top
- search.suggest
- search.highlight
- content.code.copy
markdown_extensions:
- pymdownx.highlight
- pymdownx.superfences
- admonition
- attr_list
- def_list
- footnotes
- meta
- toc:
permalink: true
- pymdownx.arithmatex:
generic: true
- pymdownx.betterem:
smart_enable: all
- pymdownx.caret
- pymdownx.details
- pymdownx.emoji:
emoji_index: !!python/name:material.extensions.emoji.twemoji
emoji_generator: !!python/name:material.extensions.emoji.to_svg
- pymdownx.highlight:
anchor_linenums: true
- pymdownx.inlinehilite
- pymdownx.keys
- pymdownx.magiclink
- pymdownx.mark
- pymdownx.smartsymbols
- pymdownx.superfences:
custom_fences:
- name: mermaid
class: mermaid
format: !!python/name:pymdownx.superfences.fence_code_format
- pymdownx.tabbed:
alternate_style: true
- pymdownx.tasklist:
custom_checkbox: true
- pymdownx.tilde
plugins:
- search
- git-revision-date-localized:
type: date
- mkdocstrings:
default_handler: python
handlers:
python:
options:
show_source: true
nav:
- Home: index.md
- Getting Started:
- Installation: getting-started/installation.md
- Configuration: getting-started/configuration.md
- Usage: usage.md
- Quick Start: getting-started/quickstart.md
- API Reference:
- Overview: api/index.md
- SSE API: api/sse.md
- Core Functions: api/core.md
- Architecture: architecture.md
- Contributing: contributing.md
- Troubleshooting: troubleshooting.md
extra:
social:
- icon: fontawesome/brands/github
link: https://github.com/jango-blockchained/homeassistant-mcp
- icon: fontawesome/brands/docker
link: https://hub.docker.com/r/jangoblockchained/homeassistant-mcp
analytics:
provider: google
property: !ENV GOOGLE_ANALYTICS_KEY
extra_css:
- assets/stylesheets/extra.css
copyright: Copyright &copy; 2024 Jango Blockchained

View File

@@ -21,7 +21,7 @@
"profile": "bun --inspect src/index.ts",
"clean": "rm -rf dist .bun coverage",
"typecheck": "bun x tsc --noEmit",
"preinstall": "bun install --frozen-lockfile"
"example:speech": "bun run examples/speech-to-text-example.ts"
},
"dependencies": {
"@elysiajs/cors": "^1.2.0",
@@ -37,6 +37,8 @@
"node-fetch": "^3.3.2",
"sanitize-html": "^2.11.0",
"typescript": "^5.3.3",
"winston": "^3.11.0",
"winston-daily-rotate-file": "^5.0.0",
"ws": "^8.16.0",
"zod": "^3.22.4"
},

21
scripts/start_mcp.cmd Normal file
View File

@@ -0,0 +1,21 @@
@echo off
setlocal
:: Set environment variables
set NODE_ENV=production
:: Change to the script's directory
cd /d "%~dp0"
cd ..
:: Start the MCP server
echo Starting Home Assistant MCP Server...
bun run start --port 8080
if errorlevel 1 (
echo Error starting MCP server
pause
exit /b 1
)
pause

28
smithery.yaml Normal file
View File

@@ -0,0 +1,28 @@
# Smithery configuration file: https://smithery.ai/docs/config#smitheryyaml
startCommand:
type: stdio
configSchema:
# JSON Schema defining the configuration options for the MCP.
type: object
required:
- hassToken
properties:
hassToken:
type: string
description: The token for connecting to Home Assistant API.
port:
type: number
default: 4000
description: The port on which the MCP server will run.
commandFunction:
# A function that produces the CLI command to start the MCP on stdio.
|-
config => ({
command: 'bun',
args: ['--smol', 'run', 'start'],
env: {
HASS_TOKEN: config.hassToken,
PORT: config.port.toString()
}
})

View File

@@ -24,7 +24,7 @@ config({ path: resolve(process.cwd(), envFile) });
*/
export const AppConfigSchema = z.object({
/** Server Configuration */
PORT: z.number().default(4000),
PORT: z.coerce.number().default(4000),
NODE_ENV: z
.enum(["development", "production", "test"])
.default("development"),
@@ -33,6 +33,21 @@ export const AppConfigSchema = z.object({
HASS_HOST: z.string().default("http://192.168.178.63:8123"),
HASS_TOKEN: z.string().optional(),
/** Speech Features Configuration */
SPEECH: z.object({
ENABLED: z.boolean().default(false),
WAKE_WORD_ENABLED: z.boolean().default(false),
SPEECH_TO_TEXT_ENABLED: z.boolean().default(false),
WHISPER_MODEL_PATH: z.string().default("/models"),
WHISPER_MODEL_TYPE: z.string().default("base"),
}).default({
ENABLED: false,
WAKE_WORD_ENABLED: false,
SPEECH_TO_TEXT_ENABLED: false,
WHISPER_MODEL_PATH: "/models",
WHISPER_MODEL_TYPE: "base",
}),
/** Security Configuration */
JWT_SECRET: z.string().default("your-secret-key"),
RATE_LIMIT: z.object({
@@ -113,4 +128,11 @@ export const APP_CONFIG = AppConfigSchema.parse({
LOG_REQUESTS: process.env.LOG_REQUESTS === "true",
},
VERSION: "0.1.0",
SPEECH: {
ENABLED: process.env.ENABLE_SPEECH_FEATURES === "true",
WAKE_WORD_ENABLED: process.env.ENABLE_WAKE_WORD === "true",
SPEECH_TO_TEXT_ENABLED: process.env.ENABLE_SPEECH_TO_TEXT === "true",
WHISPER_MODEL_PATH: process.env.WHISPER_MODEL_PATH || "/models",
WHISPER_MODEL_TYPE: process.env.WHISPER_MODEL_TYPE || "base",
},
});

View File

@@ -25,6 +25,8 @@ import {
climateCommands,
type Command,
} from "./commands.js";
import { speechService } from "./speech/index.js";
import { APP_CONFIG } from "./config/app.config.js";
// Load environment variables based on NODE_ENV
const envFile =
@@ -129,8 +131,19 @@ app.get("/health", () => ({
status: "ok",
timestamp: new Date().toISOString(),
version: "0.1.0",
speech_enabled: APP_CONFIG.SPEECH.ENABLED,
wake_word_enabled: APP_CONFIG.SPEECH.WAKE_WORD_ENABLED,
speech_to_text_enabled: APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED,
}));
// Initialize speech service if enabled
if (APP_CONFIG.SPEECH.ENABLED) {
console.log("Initializing speech service...");
speechService.initialize().catch((error) => {
console.error("Failed to initialize speech service:", error);
});
}
// Create API endpoints for each tool
tools.forEach((tool) => {
app.post(`/api/tools/${tool.name}`, async ({ body }: { body: Record<string, unknown> }) => {
@@ -145,7 +158,12 @@ app.listen(PORT, () => {
});
// Handle server shutdown
process.on("SIGTERM", () => {
process.on("SIGTERM", async () => {
console.log("Received SIGTERM. Shutting down gracefully...");
if (APP_CONFIG.SPEECH.ENABLED) {
await speechService.shutdown().catch((error) => {
console.error("Error shutting down speech service:", error);
});
}
process.exit(0);
});

View File

View File

@@ -0,0 +1,116 @@
import { SpeechToText, WakeWordEvent, TranscriptionError } from '../speechToText';
import fs from 'fs';
import path from 'path';
describe('SpeechToText', () => {
let speechToText: SpeechToText;
const testAudioDir = path.join(__dirname, 'test_audio');
beforeEach(() => {
speechToText = new SpeechToText('fast-whisper');
// Create test audio directory if it doesn't exist
if (!fs.existsSync(testAudioDir)) {
fs.mkdirSync(testAudioDir, { recursive: true });
}
});
afterEach(() => {
speechToText.stopWakeWordDetection();
// Clean up test files
if (fs.existsSync(testAudioDir)) {
fs.rmSync(testAudioDir, { recursive: true, force: true });
}
});
describe('checkHealth', () => {
it('should handle Docker not being available', async () => {
const isHealthy = await speechToText.checkHealth();
expect(isHealthy).toBeDefined();
expect(isHealthy).toBe(false);
});
});
describe('wake word detection', () => {
it('should detect new audio files and emit wake word events', (done) => {
const testFile = path.join(testAudioDir, 'wake_word_test_123456.wav');
const testMetadata = `${testFile}.json`;
speechToText.startWakeWordDetection(testAudioDir);
speechToText.on('wake_word', (event: WakeWordEvent) => {
expect(event).toBeDefined();
expect(event.audioFile).toBe(testFile);
expect(event.metadataFile).toBe(testMetadata);
expect(event.timestamp).toBe('123456');
done();
});
// Create a test audio file to trigger the event
fs.writeFileSync(testFile, 'test audio content');
}, 1000);
it('should handle transcription errors when Docker is not available', (done) => {
const testFile = path.join(testAudioDir, 'wake_word_test_123456.wav');
let errorEmitted = false;
let wakeWordEmitted = false;
const checkDone = () => {
if (errorEmitted && wakeWordEmitted) {
done();
}
};
speechToText.on('error', (error) => {
expect(error).toBeDefined();
expect(error).toBeInstanceOf(TranscriptionError);
expect(error.message).toContain('Failed to start Docker process');
errorEmitted = true;
checkDone();
});
speechToText.on('wake_word', () => {
wakeWordEmitted = true;
checkDone();
});
speechToText.startWakeWordDetection(testAudioDir);
// Create a test audio file to trigger the event
fs.writeFileSync(testFile, 'test audio content');
}, 1000);
});
describe('transcribeAudio', () => {
it('should handle Docker not being available for transcription', async () => {
await expect(
speechToText.transcribeAudio('/audio/test.wav')
).rejects.toThrow(TranscriptionError);
});
it('should emit progress events on error', (done) => {
let progressEmitted = false;
let errorThrown = false;
const checkDone = () => {
if (progressEmitted && errorThrown) {
done();
}
};
speechToText.on('progress', (event: { type: string; data: string }) => {
expect(event.type).toBe('stderr');
expect(event.data).toBe('Failed to start Docker process');
progressEmitted = true;
checkDone();
});
speechToText.transcribeAudio('/audio/test.wav')
.catch((error) => {
expect(error).toBeInstanceOf(TranscriptionError);
errorThrown = true;
checkDone();
});
}, 1000);
});
});

110
src/speech/index.ts Normal file
View File

@@ -0,0 +1,110 @@
import { APP_CONFIG } from "../config/app.config.js";
import { logger } from "../utils/logger.js";
import type { IWakeWordDetector, ISpeechToText } from "./types.js";
class SpeechService {
private static instance: SpeechService | null = null;
private isInitialized: boolean = false;
private wakeWordDetector: IWakeWordDetector | null = null;
private speechToText: ISpeechToText | null = null;
private constructor() { }
public static getInstance(): SpeechService {
if (!SpeechService.instance) {
SpeechService.instance = new SpeechService();
}
return SpeechService.instance;
}
public async initialize(): Promise<void> {
if (this.isInitialized) {
return;
}
if (!APP_CONFIG.SPEECH.ENABLED) {
logger.info("Speech features are disabled. Skipping initialization.");
return;
}
try {
// Initialize components based on configuration
if (APP_CONFIG.SPEECH.WAKE_WORD_ENABLED) {
logger.info("Initializing wake word detection...");
// Dynamic import to avoid loading the module if not needed
const { WakeWordDetector } = await import("./wakeWordDetector.js");
this.wakeWordDetector = new WakeWordDetector() as IWakeWordDetector;
await this.wakeWordDetector.initialize();
}
if (APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED) {
logger.info("Initializing speech-to-text...");
// Dynamic import to avoid loading the module if not needed
const { SpeechToText } = await import("./speechToText.js");
this.speechToText = new SpeechToText({
modelPath: APP_CONFIG.SPEECH.WHISPER_MODEL_PATH,
modelType: APP_CONFIG.SPEECH.WHISPER_MODEL_TYPE,
}) as ISpeechToText;
await this.speechToText.initialize();
}
this.isInitialized = true;
logger.info("Speech service initialized successfully");
} catch (error) {
logger.error("Failed to initialize speech service:", error);
throw error;
}
}
public async shutdown(): Promise<void> {
if (!this.isInitialized) {
return;
}
try {
if (this.wakeWordDetector) {
await this.wakeWordDetector.shutdown();
this.wakeWordDetector = null;
}
if (this.speechToText) {
await this.speechToText.shutdown();
this.speechToText = null;
}
this.isInitialized = false;
logger.info("Speech service shut down successfully");
} catch (error) {
logger.error("Error during speech service shutdown:", error);
throw error;
}
}
public isEnabled(): boolean {
return APP_CONFIG.SPEECH.ENABLED;
}
public isWakeWordEnabled(): boolean {
return APP_CONFIG.SPEECH.WAKE_WORD_ENABLED;
}
public isSpeechToTextEnabled(): boolean {
return APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED;
}
public getWakeWordDetector(): IWakeWordDetector {
if (!this.isInitialized || !this.wakeWordDetector) {
throw new Error("Wake word detector is not initialized");
}
return this.wakeWordDetector;
}
public getSpeechToText(): ISpeechToText {
if (!this.isInitialized || !this.speechToText) {
throw new Error("Speech-to-text is not initialized");
}
return this.speechToText;
}
}
export const speechService = SpeechService.getInstance();

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import { spawn } from 'child_process';
import { EventEmitter } from 'events';
import { watch } from 'fs';
import path from 'path';
import { ISpeechToText, SpeechToTextConfig } from "./types.js";
export interface TranscriptionOptions {
model?: 'tiny.en' | 'base.en' | 'small.en' | 'medium.en' | 'large-v2';
language?: string;
temperature?: number;
beamSize?: number;
patience?: number;
device?: 'cpu' | 'cuda';
}
export interface TranscriptionResult {
text: string;
segments: Array<{
text: string;
start: number;
end: number;
confidence: number;
}>;
}
export interface WakeWordEvent {
timestamp: string;
audioFile: string;
metadataFile: string;
}
export class TranscriptionError extends Error {
constructor(message: string) {
super(message);
this.name = 'TranscriptionError';
}
}
export class SpeechToText extends EventEmitter implements ISpeechToText {
private containerName: string;
private audioWatcher?: ReturnType<typeof watch>;
private modelPath: string;
private modelType: string;
private isInitialized: boolean = false;
constructor(config: SpeechToTextConfig) {
super();
this.containerName = config.containerName || 'fast-whisper';
this.modelPath = config.modelPath;
this.modelType = config.modelType;
}
public async initialize(): Promise<void> {
if (this.isInitialized) {
return;
}
try {
// Initialization logic will be implemented here
await this.setupContainer();
this.isInitialized = true;
this.emit('ready');
} catch (error) {
this.emit('error', error);
throw error;
}
}
public async shutdown(): Promise<void> {
if (!this.isInitialized) {
return;
}
try {
// Cleanup logic will be implemented here
await this.cleanupContainer();
this.isInitialized = false;
this.emit('shutdown');
} catch (error) {
this.emit('error', error);
throw error;
}
}
public async transcribe(audioData: Buffer): Promise<string> {
if (!this.isInitialized) {
throw new Error("Speech-to-text service is not initialized");
}
try {
// Transcription logic will be implemented here
this.emit('transcribing');
const result = await this.processAudio(audioData);
this.emit('transcribed', result);
return result;
} catch (error) {
this.emit('error', error);
throw error;
}
}
private async setupContainer(): Promise<void> {
// Container setup logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
private async cleanupContainer(): Promise<void> {
// Container cleanup logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
private async processAudio(audioData: Buffer): Promise<string> {
// Audio processing logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
return "Transcription placeholder";
}
startWakeWordDetection(audioDir: string = './audio'): void {
// Watch for new audio files from wake word detection
this.audioWatcher = watch(audioDir, (eventType, filename) => {
if (eventType === 'rename' && filename && filename.startsWith('wake_word_') && filename.endsWith('.wav')) {
const audioFile = path.join(audioDir, filename);
const metadataFile = `${audioFile}.json`;
const parts = filename.split('_');
const timestamp = parts[parts.length - 1].split('.')[0];
// Emit wake word event
this.emit('wake_word', {
timestamp,
audioFile,
metadataFile
} as WakeWordEvent);
// Automatically transcribe the wake word audio
this.transcribeAudio(audioFile)
.then(result => {
this.emit('transcription', { audioFile, result });
})
.catch(error => {
this.emit('error', error);
});
}
});
}
stopWakeWordDetection(): void {
if (this.audioWatcher) {
this.audioWatcher.close();
this.audioWatcher = undefined;
}
}
async transcribeAudio(
audioFilePath: string,
options: TranscriptionOptions = {}
): Promise<TranscriptionResult> {
const {
model = 'base.en',
language = 'en',
temperature = 0,
beamSize = 5,
patience = 1,
device = 'cpu'
} = options;
return new Promise((resolve, reject) => {
const args = [
'exec',
this.containerName,
'fast-whisper',
'--model', model,
'--language', language,
'--temperature', temperature.toString(),
'--beam-size', beamSize.toString(),
'--patience', patience.toString(),
'--device', device,
'--output-json',
audioFilePath
];
let process;
try {
process = spawn('docker', args);
} catch (error) {
this.emit('progress', { type: 'stderr', data: 'Failed to start Docker process' });
reject(new TranscriptionError('Failed to start Docker process'));
return;
}
let stdout = '';
let stderr = '';
process.stdout?.on('data', (data: Buffer) => {
stdout += data.toString();
this.emit('progress', { type: 'stdout', data: data.toString() });
});
process.stderr?.on('data', (data: Buffer) => {
stderr += data.toString();
this.emit('progress', { type: 'stderr', data: data.toString() });
});
process.on('error', (error: Error) => {
this.emit('progress', { type: 'stderr', data: error.message });
reject(new TranscriptionError(`Failed to execute Docker command: ${error.message}`));
});
process.on('close', (code: number) => {
if (code !== 0) {
reject(new TranscriptionError(`Transcription failed: ${stderr}`));
return;
}
try {
const result = JSON.parse(stdout) as TranscriptionResult;
resolve(result);
} catch (error: unknown) {
if (error instanceof Error) {
reject(new TranscriptionError(`Failed to parse transcription result: ${error.message}`));
} else {
reject(new TranscriptionError('Failed to parse transcription result: Unknown error'));
}
}
});
});
}
async checkHealth(): Promise<boolean> {
try {
const process = spawn('docker', ['ps', '--filter', `name=${this.containerName}`, '--format', '{{.Status}}']);
return new Promise((resolve) => {
let output = '';
process.stdout?.on('data', (data: Buffer) => {
output += data.toString();
});
process.on('error', () => {
resolve(false);
});
process.on('close', (code: number) => {
resolve(code === 0 && output.toLowerCase().includes('up'));
});
});
} catch (error) {
return false;
}
}
}

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import { EventEmitter } from "events";
export interface IWakeWordDetector {
initialize(): Promise<void>;
shutdown(): Promise<void>;
startListening(): Promise<void>;
stopListening(): Promise<void>;
}
export interface ISpeechToText extends EventEmitter {
initialize(): Promise<void>;
shutdown(): Promise<void>;
transcribe(audioData: Buffer): Promise<string>;
}
export interface SpeechToTextConfig {
modelPath: string;
modelType: string;
containerName?: string;
}

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import { IWakeWordDetector } from "./types.js";
export class WakeWordDetector implements IWakeWordDetector {
private isListening: boolean = false;
private isInitialized: boolean = false;
public async initialize(): Promise<void> {
if (this.isInitialized) {
return;
}
// Initialization logic will be implemented here
await this.setupDetector();
this.isInitialized = true;
}
public async shutdown(): Promise<void> {
if (this.isListening) {
await this.stopListening();
}
if (this.isInitialized) {
await this.cleanupDetector();
this.isInitialized = false;
}
}
public async startListening(): Promise<void> {
if (!this.isInitialized) {
throw new Error("Wake word detector is not initialized");
}
if (this.isListening) {
return;
}
await this.startDetection();
this.isListening = true;
}
public async stopListening(): Promise<void> {
if (!this.isListening) {
return;
}
await this.stopDetection();
this.isListening = false;
}
private async setupDetector(): Promise<void> {
// Setup logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
private async cleanupDetector(): Promise<void> {
// Cleanup logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
private async startDetection(): Promise<void> {
// Start detection logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
private async stopDetection(): Promise<void> {
// Stop detection logic will be implemented here
await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
}
}