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docs: Update environment configuration and README with comprehensive setup guide

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- Enhance `.env.example` with more detailed and organized configuration options
- Refactor README to provide clearer setup instructions and system architecture overview
- Add new `scripts/setup-env.sh` for flexible environment configuration management
- Update `docs/configuration.md` with detailed environment loading strategy and best practices
- Improve documentation for speech features, client integration, and development workflows
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2025-02-06 09:35:02 +01:00
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# MCP Server for Home Assistant 🏠🤖
[![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) [![smithery badge](https://smithery.ai/badge/@jango-blockchained/advanced-homeassistant-mcp)](https://smithery.ai/server/@jango-blockchained/advanced-homeassistant-mcp)
[![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)
## Overview 🌐
MCP (Model Context Protocol) Server is a lightweight integration tool for Home Assistant, providing a flexible interface for device management and automation.
MCP (Model Context Protocol) Server is my lightweight integration tool for Home Assistant, providing a flexible interface for device management and automation. It's designed to be fast, secure, and easy to use. Built with Bun for maximum performance.
## Why Bun? 🚀
I chose Bun as the runtime for several key benefits:
- ⚡ **Blazing Fast Performance**
- Up to 4x faster than Node.js
- Built-in TypeScript support
- Optimized file system operations
- 🎯 **All-in-One Solution**
- Package manager (faster than npm/yarn)
- Bundler (no webpack needed)
- Test runner (built-in testing)
- TypeScript transpiler
- 🔋 **Built-in Features**
- SQLite3 driver
- .env file loading
- WebSocket client/server
- File watcher
- Test runner
- 💾 **Resource Efficient**
- Lower memory usage
- Faster cold starts
- Better CPU utilization
- 🔄 **Node.js Compatibility**
- Runs most npm packages
- Compatible with Express/Fastify
- Native Node.js APIs
## Core Features ✨
@@ -12,95 +44,131 @@ MCP (Model Context Protocol) Server is a lightweight integration tool for Home A
- 📡 WebSocket/Server-Sent Events (SSE) for state updates
- 🤖 Simple automation rule management
- 🔐 JWT-based authentication
- 🎤 Real-time device control and monitoring
- 🎤 Server-Sent Events (SSE) for live updates
- 🎤 Comprehensive logging
- 🎤 Optional speech features:
- 🎤 Wake word detection ("hey jarvis", "ok google", "alexa")
- 🎤 Speech-to-text using fast-whisper
- 🎤 Multiple language support
- 🎤 GPU acceleration support
- 🗣️ Wake word detection ("hey jarvis", "ok google", "alexa")
- 🎯 Speech-to-text using fast-whisper
- 🌍 Multiple language support
- 🚀 GPU acceleration support
## System Architecture 📊
```mermaid
flowchart TB
subgraph Client["Client Applications"]
direction TB
Web["Web Interface"]
Mobile["Mobile Apps"]
Voice["Voice Control"]
end
subgraph MCP["MCP Server"]
direction TB
API["REST API"]
WS["WebSocket/SSE"]
Auth["Authentication"]
subgraph Speech["Speech Processing (Optional)"]
direction TB
Wake["Wake Word Detection"]
STT["Speech-to-Text"]
subgraph STT_Options["STT Options"]
direction LR
Whisper["Whisper"]
FastWhisper["Fast Whisper"]
end
Wake --> STT
STT --> STT_Options
end
end
subgraph HA["Home Assistant"]
direction TB
HASS_API["HASS API"]
HASS_WS["HASS WebSocket"]
Devices["Smart Devices"]
end
Client --> MCP
MCP --> HA
HA --> Devices
style Speech fill:#f9f,stroke:#333,stroke-width:2px
style STT_Options fill:#bbf,stroke:#333,stroke-width:1px
```
## Prerequisites 📋
- 🚀 Bun runtime (v1.0.26+)
- 🏡 Home Assistant instance
- 🐳 Docker (optional, recommended for deployment and speech features)
- 🚀 [Bun runtime](https://bun.sh) (v1.0.26+)
- 🏡 [Home Assistant](https://www.home-assistant.io/) instance
- 🐳 Docker (optional, recommended for deployment)
- 🖥️ Node.js 18+ (optional, for speech features)
- 🖥️ NVIDIA GPU with CUDA support (optional, for faster speech processing)
- 🎮 NVIDIA GPU with CUDA support (optional, for faster speech processing)
## Installation 🛠️
### Docker Deployment (Recommended)
## Quick Start 🚀
1. Clone my repository:
```bash
# Clone the repository
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
# Copy environment template:
cp .env.example .env
# Edit .env with your Home Assistant credentials and speech features settings
# Build and start containers
docker compose up -d --build
```
### Bare Metal Installation
2. Set up the environment:
```bash
# Install Bun
curl -fsSL https://bun.sh/install | bash
# Make my setup script executable
chmod +x scripts/setup-env.sh
# Clone the repository
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp
# Run setup (defaults to development)
./scripts/setup-env.sh
# Install dependencies
bun install
# Or specify an environment:
NODE_ENV=production ./scripts/setup-env.sh
# Start the server
bun run dev
# Force override existing files:
./scripts/setup-env.sh --force
```
## Basic Usage 🖥️
3. Configure your settings:
- Edit `.env` file with your Home Assistant details
- Required: Add your `HASS_TOKEN` (long-lived access token)
### Device Control Example
```typescript
// Turn on a light
const response = await fetch('http://localhost:3000/api/devices/light.living_room', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${token}`
},
body: JSON.stringify({ state: 'on' })
});
4. Launch with Docker:
```bash
docker compose up -d
```
### WebSocket State Updates
## Environment Configuration 🔧
```typescript
const ws = new WebSocket('ws://localhost:3000/devices');
ws.onmessage = (event) => {
const deviceState = JSON.parse(event.data);
console.log('Device state updated:', deviceState);
};
```
I've implemented a hierarchical configuration system:
## Speech Features (Optional)
### File Structure 📁
1. `.env.example` - My template with all options
2. `.env` - Your configuration (copy from .env.example)
3. Environment overrides:
- `.env.dev` - Development settings
- `.env.prod` - Production settings
- `.env.test` - Test settings
The MCP Server includes optional speech processing capabilities:
### Loading Priority ⚡
Files load in this order:
1. `.env` (base config)
2. Environment-specific file:
- `NODE_ENV=development` → `.env.dev`
- `NODE_ENV=production` → `.env.prod`
- `NODE_ENV=test` → `.env.test`
Later files override earlier ones.
## Speech Features Setup 🎤
### Prerequisites
1. Docker installed and running
2. NVIDIA GPU with CUDA support (optional)
3. At least 4GB RAM (8GB+ recommended for larger models)
1. 🐳 Docker installed and running
2. 🎮 NVIDIA GPU with CUDA (optional)
3. 💾 4GB+ RAM (8GB+ recommended)
### Setup
1. Enable speech features in your .env:
### Configuration
1. Enable speech in `.env`:
```bash
ENABLE_SPEECH_FEATURES=true
ENABLE_WAKE_WORD=true
@@ -109,67 +177,65 @@ WHISPER_MODEL_PATH=/models
WHISPER_MODEL_TYPE=base
```
2. Start the speech services:
2. Choose your STT engine:
```bash
docker-compose up -d
# For standard Whisper
STT_ENGINE=whisper
# For Fast Whisper (GPU recommended)
STT_ENGINE=fast-whisper
CUDA_VISIBLE_DEVICES=0 # Set GPU device
```
### Available Models
Choose a model based on your needs:
### Available Models 🤖
Choose based on your needs:
- `tiny.en`: Fastest, basic accuracy
- `base.en`: Good balance (recommended)
- `small.en`: Better accuracy, slower
- `medium.en`: High accuracy, resource intensive
- `large-v2`: Best accuracy, very resource intensive
### Usage
## Development 💻
1. Wake word detection listens for:
- "hey jarvis"
- "ok google"
- "alexa"
```bash
# Install dependencies
bun install
2. After wake word detection:
- Audio is automatically captured
- Speech is transcribed
- Commands are processed
# Run in development mode
bun run dev
3. Manual transcription is also available:
```typescript
const speech = speechService.getSpeechToText();
const text = await speech.transcribe(audioBuffer);
# Run tests
bun test
# Run with hot reload
bun --hot run dev
# Build for production
bun build ./src/index.ts --target=bun
# Run production build
bun run start
```
## Configuration
### Performance Comparison 📊
See [Configuration Guide](docs/configuration.md) for detailed settings.
| Operation | Bun | Node.js |
|-----------|-----|---------|
| Install Dependencies | ~2s | ~15s |
| Cold Start | 300ms | 1000ms |
| Build Time | 150ms | 4000ms |
| Memory Usage | ~150MB | ~400MB |
## API Documentation
## Documentation 📚
See [API Documentation](docs/api/index.md) for available endpoints.
- [Configuration Guide](docs/configuration.md)
- [API Documentation](docs/api.md)
- [Troubleshooting](docs/troubleshooting.md)
## Development
See [Development Guide](docs/development/index.md) for contribution guidelines.
## License 📄
MIT License. See [LICENSE](LICENSE) for details.
## Support 🆘
- 🐞 [GitHub Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues)
- 📖 Documentation: [Project Docs](https://jango-blockchained.github.io/homeassistant-mcp/)
## 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:
## Client Integration 🔗
### Cursor Integration 🖱️
The server can be integrated with Cursor by adding the configuration to `.cursor/config/config.json`:
Add to `.cursor/config/config.json`:
```json
{
"mcpServers": {
@@ -185,10 +251,8 @@ The server can be integrated with Cursor by adding the configuration to `.cursor
}
```
### Claude Desktop Integration 💬
For Claude Desktop, add the following to your Claude configuration file:
### Claude Desktop 💬
Add to your Claude config:
```json
{
"mcpServers": {
@@ -203,37 +267,15 @@ For Claude Desktop, add the following to your Claude configuration file:
}
```
### Cline Integration 📟
For Cline-based clients, add the following configuration:
```json
{
"mcpServers": {
"homeassistant-mcp": {
"command": "bun",
"args": [
"run",
"start",
"--enable-cline",
"--config",
"${configDir}/.env"
],
"env": {
"NODE_ENV": "production",
"CLINE_MODE": "true"
}
}
}
}
```
### Command Line Usage 💻
#### Windows
A CMD script is provided in the `scripts` directory. To use it:
1. Navigate to the `scripts` directory
### Command Line 💻
Windows users can use the provided script:
1. Go to `scripts` directory
2. Run `start_mcp.cmd`
The script will start the MCP server with default configuration.
## License 📄
MIT License. See [LICENSE](LICENSE) for details.
## Author 👨‍💻
Created by [jango-blockchained](https://github.com/jango-blockchained)