Model Context Protocol Server for Home Assistant

The server uses the MCP protocol to share access to a local Home Assistant instance with an LLM application.

A powerful bridge between your Home Assistant instance and Language Learning Models (LLMs), enabling natural language control and monitoring of your smart home devices through the Model Context Protocol (MCP). This server provides a comprehensive API for managing your entire Home Assistant ecosystem, from device control to system administration.

Features

• 🎮 Device Control: Control any Home Assistant device through natural language
• 🔄 Real-time Updates: Get instant updates through Server-Sent Events (SSE)
• 🤖 Automation Management: Create, update, and manage automations
• 📊 State Monitoring: Track and query device states
• 🔐 Secure: Token-based authentication and rate limiting
• 📱 Mobile Ready: Works with any HTTP-capable client

Real-time Updates with SSE

The server includes a powerful Server-Sent Events (SSE) system that provides real-time updates from your Home Assistant instance. This allows you to:

• 🔄 Get instant state changes for any device
• 📡 Monitor automation triggers and executions
• 🎯 Subscribe to specific domains or entities
• 📊 Track service calls and script executions

Quick SSE Example

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);
};

See SSE_API.md for complete documentation of the SSE system.

Table of Contents

• Key Features
• Prerequisites
• Installation
  • Basic Setup
  • Docker Setup (Recommended)
• Configuration
• Development
• API Reference
  • MCP Schema
  • Device Control
  • Add-on Management
  • Package Management
  • Automation Management
• OpenAI Integration
  • Standard Analysis
  • Custom Prompt Analysis
• Natural Language Integration
• Troubleshooting
• Project Status
• Contributing
• Resources
• License

Key Features

Core Functionality 🎮

• Smart Device Control
  • 💡 Lights: Brightness, color temperature, RGB color
  • 🌡️ Climate: Temperature, HVAC modes, fan modes, humidity
  • 🚪 Covers: Position and tilt control
  • 🔌 Switches: On/off control
  • 🚨 Sensors & Contacts: State monitoring
  • 🎵 Media Players: Playback control, volume, source selection
  • 🌪️ Fans: Speed, oscillation, direction
  • 🔒 Locks: Lock/unlock control
  • 🧹 Vacuums: Start, stop, return to base
  • 📹 Cameras: Motion detection, snapshots

System Management 🛠️

• Add-on Management

  • Browse available add-ons
  • Install/uninstall add-ons
  • Start/stop/restart add-ons
  • Version management
  • Configuration access

• Package Management (HACS)

  • Integration with Home Assistant Community Store
  • Multiple package types support:
    • Custom integrations
    • Frontend themes
    • Python scripts
    • AppDaemon apps
    • NetDaemon apps
  • Version control and updates
  • Repository management

• Automation Management

  • Create and edit automations
  • Advanced configuration options:
    • Multiple trigger types
    • Complex conditions
    • Action sequences
    • Execution modes
  • Duplicate and modify existing automations
  • Enable/disable automation rules
  • Trigger automation manually

Architecture Features 🏗️

• Intelligent Organization

  • Area and floor-based device grouping
  • State monitoring and querying
  • Smart context awareness
  • Historical data access

• Robust Architecture

  • Comprehensive error handling
  • State validation
  • Secure API integration
  • TypeScript type safety
  • Extensive test coverage

Prerequisites

• Node.js 20.10.0 or higher
• NPM package manager
• Docker Compose for containerization
• Running Home Assistant instance
• Home Assistant long-lived access token (How to get token)
• HACS installed for package management features
• Supervisor access for add-on management

Installation

Basic Setup

# Clone the repository
git clone https://github.com/jango-blockchained/homeassistant-mcp.git
cd homeassistant-mcp

# Install dependencies
npm install

# Build the project
npm run build

Docker Setup (Recommended)

The project includes Docker support for easy deployment and consistent environments across different platforms.

1. Clone the repository:

   git clone https://github.com/jango-blockchained/homeassistant-mcp.git
   cd homeassistant-mcp
   

2. Configure environment:

   cp .env.example .env
   

   Edit the .env file with your Home Assistant configuration:

   # Home Assistant Configuration
   HASS_HOST=http://homeassistant.local:8123
   HASS_TOKEN=your_home_assistant_token
   HASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket
   
   # Server Configuration
   PORT=3000
   NODE_ENV=production
   DEBUG=false
   

3. Build and run with Docker Compose:

   # Build and start the containers
   docker compose up -d
   
   # View logs
   docker compose logs -f
   
   # Stop the service
   docker compose down
   

4. Verify the installation: The server should now be running at http://localhost:3000. You can check the health endpoint at http://localhost:3000/health.

5. Update the application:

   # Pull the latest changes
   git pull
   
   # Rebuild and restart the containers
   docker compose up -d --build
   

Docker Configuration

The Docker setup includes:

• Multi-stage build for optimal image size
• Health checks for container monitoring
• Volume mounting for environment configuration
• Automatic container restart on failure
• Exposed port 3000 for API access

Docker Compose Environment Variables

All environment variables can be configured in the .env file. The following variables are supported:

• HASS_HOST: Your Home Assistant instance URL
• HASS_TOKEN: Long-lived access token for Home Assistant
• HASS_SOCKET_URL: WebSocket URL for Home Assistant
• PORT: Server port (default: 3000)
• NODE_ENV: Environment (production/development)
• DEBUG: Enable debug mode (true/false)

Configuration

Environment Variables

# Home Assistant Configuration
HASS_HOST=http://homeassistant.local:8123  # Your Home Assistant instance URL
HASS_TOKEN=your_home_assistant_token       # Long-lived access token
HASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket  # WebSocket URL

# Server Configuration
PORT=3000                # Server port (default: 3000)
NODE_ENV=production     # Environment (production/development)
DEBUG=false            # Enable debug mode

# Test Configuration
TEST_HASS_HOST=http://localhost:8123  # Test instance URL
TEST_HASS_TOKEN=test_token           # Test token

Configuration Files

1. Development: Copy .env.example to .env.development
2. Production: Copy .env.example to .env.production
3. Testing: Copy .env.example to .env.test

Home Assistant Analyzer CLI

The project includes a powerful command-line tool (ha-analyzer-cli.ts) for analyzing and optimizing your Home Assistant setup. This tool provides comprehensive system analysis, automation optimization, and custom querying capabilities.

Features

• 🔍 System Analysis

  • Device state monitoring
  • Health checks
  • Configuration analysis
  • Integration status
  • Performance metrics
  • Security assessment

• 🤖 Automation Analysis

  • Inefficient automation detection
  • Optimization suggestions
  • Blueprint recommendations
  • Condition optimizations

• ⚡ Performance Optimization

  • Resource usage analysis
  • Response time monitoring
  • Configuration optimization suggestions
  • Integration improvement recommendations

• 🔐 Security Analysis

  • Current security measures assessment
  • Vulnerability detection
  • Security recommendations

• 📊 Entity Usage Analysis

  • Most active entities tracking
  • Rarely used entity detection
  • Potential duplicate identification

• 💡 Energy Management

  • High consumption detection
  • Monitoring suggestions
  • Tariff optimization recommendations

Configuration

The analyzer requires the following environment variables:

OPENAI_API_KEY=your_openai_api_key    # Required for analysis
HASS_TOKEN=your_hass_token            # Home Assistant access token
MCP_SERVER=http://localhost:3000      # MCP server URL (default)
OPENAI_MODEL=gpt-4o                   # Default model (optional)
MAX_RETRIES=3                         # Max retry attempts (optional)
ANALYSIS_TIMEOUT=30000                # Analysis timeout in ms (optional)

Available Models

The analyzer supports multiple language models:

• GPT-4 Models:
  • gpt-4o: Standard GPT-4
  • gpt-4-turbo: GPT-4 Turbo
  • gpt-4: Original GPT-4
• GPT-3.5 Models:
  • gpt-3.5-turbo: Standard GPT-3.5
  • gpt-3.5-turbo-16k: Extended context GPT-3.5
• DeepSeek Models (requires DEEPSEEK_API_KEY):
  • deepseek-v3: DeepSeek v3
  • deepseek-r1: DeepSeek R1

Usage

1. Standard Analysis

npx ts-node ha-analyzer-cli.ts analyze

2. Custom Prompt Analysis

npx ts-node ha-analyzer-cli.ts custom

3. Automation Optimization

npx ts-node ha-analyzer-cli.ts optimize

The analysis results will be displayed in a structured format, organized by categories such as system overview, performance, security, optimization suggestions, and more.

API Reference

MCP Schema Endpoint

The server exposes an MCP (Model Context Protocol) schema endpoint that describes all available tools and their parameters:

GET /mcp

This endpoint returns a JSON schema describing all available tools, their parameters, and documentation resources. The schema follows the MCP specification and can be used by LLM clients to understand the server's capabilities.

Example response:

{
  "tools": [
    {
      "name": "list_devices",
      "description": "List all devices connected to Home Assistant",
      "parameters": {
        "type": "object",
        "properties": {
          "domain": {
            "type": "string",
            "enum": ["light", "climate", "alarm_control_panel", ...]
          },
          "area": { "type": "string" },
          "floor": { "type": "string" }
        }
      }
    },
    // ... other tools
  ],
  "prompts": [],
  "resources": [
    {
      "name": "Home Assistant API",
      "url": "https://developers.home-assistant.io/docs/api/rest/"
    }
  ]
}

Note: The /mcp endpoint is publicly accessible and does not require authentication, as it only provides schema information.

Device Control

Common Entity Controls

{
  "tool": "control",
  "command": "turn_on",  // or "turn_off", "toggle"
  "entity_id": "light.living_room"
}

Light Control

{
  "tool": "control",
  "command": "turn_on",
  "entity_id": "light.living_room",
  "brightness": 128,
  "color_temp": 4000,
  "rgb_color": [255, 0, 0]
}

Add-on Management

List Available Add-ons

{
  "tool": "addon",
  "action": "list"
}

Install Add-on

{
  "tool": "addon",
  "action": "install",
  "slug": "core_configurator",
  "version": "5.6.0"
}

Manage Add-on State

{
  "tool": "addon",
  "action": "start",  // or "stop", "restart"
  "slug": "core_configurator"
}

Package Management

List HACS Packages

{
  "tool": "package",
  "action": "list",
  "category": "integration"  // or "plugin", "theme", "python_script", "appdaemon", "netdaemon"
}

Install Package

{
  "tool": "package",
  "action": "install",
  "category": "integration",
  "repository": "hacs/integration",
  "version": "1.32.0"
}

Automation Management

Create Automation

{
  "tool": "automation_config",
  "action": "create",
  "config": {
    "alias": "Motion Light",
    "description": "Turn on light when motion detected",
    "mode": "single",
    "trigger": [
      {
        "platform": "state",
        "entity_id": "binary_sensor.motion",
        "to": "on"
      }
    ],
    "action": [
      {
        "service": "light.turn_on",
        "target": {
          "entity_id": "light.living_room"
        }
      }
    ]
  }
}

Duplicate Automation

{
  "tool": "automation_config",
  "action": "duplicate",
  "automation_id": "automation.motion_light"
}

Core Functions

State Management

GET /api/state
POST /api/state

Manages the current state of the system.

Example Request:

POST /api/state
{
  "context": "living_room",
  "state": {
    "lights": "on",
    "temperature": 22
  }
}

Context Updates

POST /api/context

Updates the current context with new information.

Example Request:

POST /api/context
{
  "user": "john",
  "location": "kitchen",
  "time": "morning",
  "activity": "cooking"
}

Action Endpoints

Execute Action

POST /api/action

Executes a specified action with given parameters.

Example Request:

POST /api/action
{
  "action": "turn_on_lights",
  "parameters": {
    "room": "living_room",
    "brightness": 80
  }
}

Batch Actions

POST /api/actions/batch

Executes multiple actions in sequence.

Example Request:

POST /api/actions/batch
{
  "actions": [
    {
      "action": "turn_on_lights",
      "parameters": {
        "room": "living_room"
      }
    },
    {
      "action": "set_temperature",
      "parameters": {
        "temperature": 22
      }
    }
  ]
}

Query Functions

Get Available Actions

GET /api/actions

Returns a list of all available actions.

Example Response:

{
  "actions": [
    {
      "name": "turn_on_lights",
      "parameters": ["room", "brightness"],
      "description": "Turns on lights in specified room"
    },
    {
      "name": "set_temperature",
      "parameters": ["temperature"],
      "description": "Sets temperature in current context"
    }
  ]
}

Context Query

GET /api/context?type=current

Retrieves context information.

Example Response:

{
  "current_context": {
    "user": "john",
    "location": "kitchen",
    "time": "morning",
    "activity": "cooking"
  }
}

WebSocket Events

The server supports real-time updates via WebSocket connections.

// Client-side connection example
const ws = new WebSocket('ws://localhost:3000/ws');

ws.onmessage = (event) => {
  const data = JSON.parse(event.data);
  console.log('Received update:', data);
};

Supported Events

• state_change: Emitted when system state changes
• context_update: Emitted when context is updated
• action_executed: Emitted when an action is completed
• error: Emitted when an error occurs

Example Event Data:

{
  "event": "state_change",
  "data": {
    "previous_state": {
      "lights": "off"
    },
    "current_state": {
      "lights": "on"
    },
    "timestamp": "2024-03-20T10:30:00Z"
  }
}

Error Handling

All endpoints return standard HTTP status codes:

• 200: Success
• 400: Bad Request
• 401: Unauthorized
• 403: Forbidden
• 404: Not Found
• 500: Internal Server Error

Error Response Format:

{
  "error": {
    "code": "INVALID_PARAMETERS",
    "message": "Missing required parameter: room",
    "details": {
      "missing_fields": ["room"]
    }
  }
}

Rate Limiting

The API implements rate limiting to prevent abuse:

• 100 requests per minute per IP for regular endpoints
• 1000 requests per minute per IP for WebSocket connections

When rate limit is exceeded, the server returns:

{
  "error": {
    "code": "RATE_LIMIT_EXCEEDED",
    "message": "Too many requests",
    "reset_time": "2024-03-20T10:31:00Z"
  }
}

Example Usage

Using curl

# Get current state
curl -X GET \
  http://localhost:3000/api/state \
  -H 'Authorization: ApiKey your_api_key_here'

# Execute action
curl -X POST \
  http://localhost:3000/api/action \
  -H 'Authorization: ApiKey your_api_key_here' \
  -H 'Content-Type: application/json' \
  -d '{
    "action": "turn_on_lights",
    "parameters": {
      "room": "living_room",
      "brightness": 80
    }
  }'

Using JavaScript

// Execute action
async function executeAction() {
  const response = await fetch('http://localhost:3000/api/action', {
    method: 'POST',
    headers: {
      'Authorization': 'ApiKey your_api_key_here',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      action: 'turn_on_lights',
      parameters: {
        room: 'living_room',
        brightness: 80
      }
    })
  });
  
  const data = await response.json();
  console.log('Action result:', data);
}

OpenAI Integration

The server includes powerful AI analysis capabilities powered by OpenAI's GPT-4 model. This feature provides intelligent analysis of your Home Assistant setup through two main modes:

1. Standard Analysis

Performs a comprehensive system analysis including:

• System Overview
• Performance Analysis
• Security Assessment
• Optimization Recommendations
• Maintenance Tasks

# Run standard analysis
npm run test:openai
# Select option 1 when prompted

2. Custom Prompt Analysis

Allows you to ask specific questions about your Home Assistant setup. The analysis can include:

• Device States
• Configuration Details
• Active Devices
• Device Attributes (brightness, temperature, etc.)

# Run custom analysis
npm run test:openai
# Select option 2 when prompted

Available Variables

When using custom prompts, you can use these variables:

• {device_count}: Total number of devices
• {device_types}: List of device types
• {device_states}: Current states of devices
• {device_examples}: Example devices and their states

Example Custom Prompts

"Show me all active lights"
"Which devices in {device_types} need maintenance?"
"Analyze my {device_count} devices and suggest automations"

Configuration

To use the OpenAI integration, you need to set up your OpenAI API key in the .env file:

OPENAI_API_KEY=your_openai_api_key

Features

• 🔍 Intelligent device state analysis
• 📊 System health assessment
• 🤖 Smart automation suggestions
• 🔧 Maintenance recommendations
• 💡 Custom query support
• 🔄 Real-time device state information

Token Usage Optimization

The analysis tool includes smart token usage optimization:

• Automatic filtering of relevant devices based on query
• Fallback to summarized data for large systems
• Intelligent attribute selection based on device types
• Automatic retry with condensed information if token limit is reached

Development

# Development mode with hot reload
npm run dev

# Build project
npm run build

# Production mode
npm run start

# Run tests
npx jest --config=jest.config.cjs

# Run tests with coverage
npx jest --coverage

# Lint code
npm run lint

# Format code
npm run format

Troubleshooting

Common Issues

1. Node.js Version (toSorted is not a function)

   • Solution: Update to Node.js 20.10.0+

   nvm install 20.10.0
   nvm use 20.10.0
   

2. Connection Issues

   • Verify Home Assistant is running
   • Check HASS_HOST accessibility
   • Validate token permissions
   • Ensure WebSocket connection for real-time updates

3. Add-on Management Issues

   • Verify Supervisor access
   • Check add-on compatibility
   • Validate system resources

4. HACS Integration Issues

   • Verify HACS installation
   • Check HACS integration status
   • Validate repository access

5. Automation Issues

   • Verify entity availability
   • Check trigger conditions
   • Validate service calls
   • Monitor execution logs

Project Status

✅ Complete

• Entity, Floor, and Area access
• Device control (Lights, Climate, Covers, Switches, Contacts)
• Add-on management system
• Package management through HACS
• Advanced automation configuration
• Basic state management
• Error handling and validation
• Docker containerization
• Jest testing setup
• TypeScript integration
• Environment variable management
• Home Assistant API integration
• Project documentation

🚧 In Progress

• WebSocket implementation for real-time updates
• Enhanced security features
• Tool organization optimization
• Performance optimization
• Resource context integration
• API documentation generation
• Multi-platform desktop integration
• Advanced error recovery
• Custom prompt testing
• Enhanced macOS integration
• Type safety improvements
• Testing coverage expansion

Contributing

1. Fork the repository
2. Create a feature branch
3. Implement your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Submit a pull request

Resources

• MCP Documentation
• Home Assistant Docs
• HA REST API
• HACS Documentation
• TypeScript Documentation

License

MIT License - See LICENSE file