Home Assistant Model Context Protocol (MCP)

A standardized protocol for AI assistants to interact with Home Assistant, providing a secure, typed, and extensible interface for controlling smart home devices.

Overview

The Model Context Protocol (MCP) server acts as a bridge between AI models (like Claude, GPT, etc.) and Home Assistant, enabling AI assistants to:

• Execute commands on Home Assistant devices
• Retrieve information about the smart home
• Stream responses for long-running operations
• Validate parameters and inputs
• Provide consistent error handling

Features

• Modular Architecture - Clean separation between transport, middleware, and tools
• Typed Interface - Fully TypeScript typed for better developer experience
• Multiple Transports:
  • Standard I/O (stdin/stdout) for CLI integration
  • HTTP/REST API with Server-Sent Events support for streaming
• Middleware System - Validation, logging, timeout, and error handling
• Built-in Tools:
  • Light control (brightness, color, etc.)
  • Climate control (thermostats, HVAC)
  • More to come...
• Extensible Plugin System - Easily add new tools and capabilities
• Streaming Responses - Support for long-running operations
• Parameter Validation - Using Zod schemas
• Claude & Cursor Integration - Ready-made utilities for AI assistants

Getting Started

Prerequisites

• Node.js 16+
• Home Assistant instance (or you can use the mock implementations for testing)

Installation

# Clone the repository
git clone https://github.com/your-repo/homeassistant-mcp.git

# Install dependencies
cd homeassistant-mcp
npm install

# Build the project
npm run build

Running the Server

# Start with standard I/O transport (for AI assistant integration)
npm start -- --stdio

# Start with HTTP transport (for API access)
npm start -- --http

# Start with both transports
npm start -- --stdio --http

Configuration

Configure the server using environment variables or a .env file:

# Server configuration
PORT=3000
NODE_ENV=development

# Execution settings
EXECUTION_TIMEOUT=30000
STREAMING_ENABLED=true

# Transport settings
USE_STDIO_TRANSPORT=true
USE_HTTP_TRANSPORT=true

# Debug and logging
DEBUG_MODE=false
DEBUG_STDIO=false
DEBUG_HTTP=false
SILENT_STARTUP=false

# CORS settings
CORS_ORIGIN=*

Architecture

The MCP server is built with a layered architecture:

1. Transport Layer - Handles communication protocols (stdio, HTTP)
2. Middleware Layer - Processes requests through a pipeline
3. Tool Layer - Implements specific functionality
4. Resource Layer - Manages stateful resources

Tools

Tools are the primary way to add functionality to the MCP server. Each tool:

• Has a unique name
• Accepts typed parameters
• Returns typed results
• Can stream partial results
• Validates inputs and outputs

Example tool registration:

import { LightsControlTool } from "./tools/homeassistant/lights.tool.js";
import { ClimateControlTool } from "./tools/homeassistant/climate.tool.js";

// Register tools
server.registerTool(new LightsControlTool());
server.registerTool(new ClimateControlTool());

API

When running with HTTP transport, the server provides a JSON-RPC 2.0 API:

• POST /api/mcp/jsonrpc - Execute a tool
• GET /api/mcp/stream - Connect to SSE stream for real-time updates
• GET /api/mcp/info - Get server information
• GET /health - Health check endpoint

Integration with AI Models

Claude Integration

import { createClaudeToolDefinitions } from "./mcp/index.js";

// Generate Claude-compatible tool definitions
const claudeTools = createClaudeToolDefinitions([
  new LightsControlTool(),
  new ClimateControlTool()
]);

// Use with Claude API
const messages = [
  { role: "user", content: "Turn on the lights in the living room" }
];

const response = await claude.messages.create({
  model: "claude-3-opus-20240229",
  messages,
  tools: claudeTools
});

Cursor Integration

To use the Home Assistant MCP server with Cursor, add the following to your .cursor/config/config.json file:

{
  "mcpServers": {
    "homeassistant-mcp": {
      "command": "bash",
      "args": ["-c", "cd ${workspaceRoot} && bun run dist/index.js --stdio 2>/dev/null | grep -E '\\{\"jsonrpc\":\"2\\.0\"'"],
      "env": {
        "NODE_ENV": "development",
        "USE_STDIO_TRANSPORT": "true",
        "DEBUG_STDIO": "true"
      }
    }
  }
}

This configuration:

1. Runs the MCP server with stdio transport
2. Redirects all stderr output to /dev/null
3. Uses grep to filter stdout for lines containing {"jsonrpc":"2.0", ensuring clean JSON-RPC output

Troubleshooting Cursor Integration

If you encounter a "failed to create client" error when using the MCP server with Cursor:

1. Make sure you're using the correct command and arguments in your Cursor configuration

   • The bash script approach ensures only valid JSON-RPC messages reach Cursor
   • Ensure the server is built by running bun run build before trying to connect

2. Ensure the server is properly outputting JSON-RPC messages to stdout:

   bun run dist/index.js --stdio 2>/dev/null | grep -E '\{"jsonrpc":"2\.0"' > json_only.txt
   

   Then examine json_only.txt to verify it contains only valid JSON-RPC messages.

3. Make sure grep is installed on your system (it should be available by default on most systems)

4. Try rebuilding the server with:

   bun run build
   

5. Enable debug mode by setting DEBUG_STDIO=true in the environment variables

If the issue persists, you can try:

1. Restarting Cursor
2. Clearing Cursor's cache (Help > Developer > Clear Cache and Reload)
3. Using a similar approach with Node.js:

   {
     "command": "bash",
     "args": ["-c", "cd ${workspaceRoot} && node dist/index.js --stdio 2>/dev/null | grep -E '\\{\"jsonrpc\":\"2\\.0\"'"]
   }
   

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

MCP Server for Home Assistant 🏠🤖

Overview 🌐

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.

Core Features ✨

• 🔌 Basic device control via REST API
• 📡 WebSocket/Server-Sent Events (SSE) for state updates
• 🤖 Simple automation rule management
• 🔐 JWT-based authentication
• 🔄 Standard I/O (stdio) transport for integration with Claude and other AI assistants

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

Prerequisites 📋

• 🚀 Bun runtime (v1.0.26+)
• 🏡 Home Assistant instance
• 🐳 Docker (optional, recommended for deployment)
• 🖥️ Node.js 18+ (optional, for speech features)
• 🎮 NVIDIA GPU with CUDA support (optional, for faster speech processing)

Quick Start 🚀

1. Clone my repository:

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

2. Set up the environment:

# Make my setup script executable
chmod +x scripts/setup-env.sh

# Run setup (defaults to development)
./scripts/setup-env.sh

# Or specify an environment:
NODE_ENV=production ./scripts/setup-env.sh

# Force override existing files:
./scripts/setup-env.sh --force

3. Configure your settings:

• Edit .env file with your Home Assistant details
• Required: Add your HASS_TOKEN (long-lived access token)

4. Build and launch with Docker:

# Standard build
./docker-build.sh

# Launch:
docker compose up -d

Docker Build Options 🐳

My Docker build script (docker-build.sh) supports different configurations:

1. Standard Build

./docker-build.sh

• Basic MCP server functionality
• REST API and WebSocket support
• No speech features

2. Speech-Enabled Build

./docker-build.sh --speech

• Includes wake word detection
• Speech-to-text capabilities
• Pulls required images:
  • onerahmet/openai-whisper-asr-webservice
  • rhasspy/wyoming-openwakeword

3. GPU-Accelerated Build

./docker-build.sh --speech --gpu

• All speech features
• CUDA GPU acceleration
• Optimized for faster processing
• Float16 compute type for better performance

Build Features

• 🔄 Automatic resource allocation
• 💾 Memory-aware building
• 📊 CPU quota management
• 🧹 Automatic cleanup
• 📝 Detailed build logs
• 📊 Build summary and status

Environment Configuration 🔧

I've implemented a hierarchical configuration system:

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

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.

Development 💻

# Install dependencies
bun install

# Run in development mode
bun run dev

# 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

Performance Comparison 📊

| Operation | Bun | Node.js | |-----------|-----|---------| | Install Dependencies | ~2s | ~15s | | Cold Start | 300ms | 1000ms | | Build Time | 150ms | 4000ms | | Memory Usage | ~150MB | ~400MB |

Documentation 📚

Core Documentation

• Configuration Guide
• API Documentation
• Troubleshooting

Advanced Features

• Natural Language Processing - AI-powered automation analysis and control
• Custom Prompts Guide - Create and customize AI behavior
• Extras & Tools - Additional utilities and advanced features

Client Integration 🔗

Cursor Integration 🖱️

Add to .cursor/config/config.json:

{
  "mcpServers": {
    "homeassistant-mcp": {
      "command": "bash",
      "args": ["-c", "cd ${workspaceRoot} && bun run dist/index.js --stdio 2>/dev/null | grep -E '\\{\"jsonrpc\":\"2\\.0\"'"],
      "env": {
        "NODE_ENV": "development",
        "USE_STDIO_TRANSPORT": "true",
        "DEBUG_STDIO": "true"
      }
    }
  }
}

Claude Desktop 💬

Add to your Claude config:

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

Command Line 💻

Windows users can use the provided script:

1. Go to scripts directory
2. Run start_mcp.cmd

Additional Features

Speech Features 🎤

MCP Server optionally supports speech processing capabilities:

• 🗣️ Wake word detection ("hey jarvis", "ok google", "alexa")
• 🎯 Speech-to-text using fast-whisper
• 🌍 Multiple language support
• 🚀 GPU acceleration support

Speech Features Setup

Prerequisites

1. 🐳 Docker installed and running
2. 🎮 NVIDIA GPU with CUDA (optional)
3. 💾 4GB+ RAM (8GB+ recommended)

Configuration

1. Enable speech in .env:

ENABLE_SPEECH_FEATURES=true
ENABLE_WAKE_WORD=true
ENABLE_SPEECH_TO_TEXT=true
WHISPER_MODEL_PATH=/models
WHISPER_MODEL_TYPE=base

2. Choose your STT engine:

# 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 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

Launch with Speech Features

# Build with speech support
./docker-build.sh --speech

# Launch with speech features:
docker compose -f docker-compose.yml -f docker-compose.speech.yml up -d

Extra Tools 🛠️

I've included several powerful tools in the extra/ directory to enhance your Home Assistant experience:

1. Home Assistant Analyzer CLI (ha-analyzer-cli.ts)

   • Deep automation analysis using AI models
   • Security vulnerability scanning
   • Performance optimization suggestions
   • System health metrics

2. Speech-to-Text Example (speech-to-text-example.ts)

   • Wake word detection
   • Speech-to-text transcription
   • Multiple language support
   • GPU acceleration support

3. Claude Desktop Setup (claude-desktop-macos-setup.sh)

   • Automated Claude Desktop installation for macOS
   • Environment configuration
   • MCP integration setup

See Extras Documentation for detailed usage instructions and examples.

License 📄

MIT License. See LICENSE for details.

Author 👨‍💻

Created by jango-blockchained

Running with Standard I/O Transport 📝

MCP Server supports a JSON-RPC 2.0 stdio transport mode for direct integration with AI assistants like Claude:

MCP Stdio Features

✅ JSON-RPC 2.0 Compatibility: Full support for the MCP protocol standard ✅ NPX Support: Run directly without installation using npx homeassistant-mcp ✅ Auto Configuration: Creates necessary directories and default configuration ✅ Cross-Platform: Works on macOS, Linux, and Windows ✅ Claude Desktop Integration: Ready to use with Claude Desktop ✅ Parameter Validation: Automatic validation of tool parameters ✅ Error Handling: Standardized error codes and handling ✅ Detailed Logging: Logs to files without polluting stdio

Option 1: Using NPX (Easiest)

Run the MCP server directly without installation using npx:

# Basic usage
npx homeassistant-mcp

# Or with environment variables
HASS_URL=http://your-ha-instance:8123 HASS_TOKEN=your_token npx homeassistant-mcp

This will:

1. Install the package temporarily
2. Automatically run in stdio mode with JSON-RPC 2.0 transport
3. Create a logs directory for logging
4. Create a default .env file if not present

Perfect for integration with Claude Desktop or other MCP clients.

Integrating with Claude Desktop

To use MCP with Claude Desktop:

1. Open Claude Desktop settings
2. Go to the "Advanced" tab
3. Under "MCP Server", select "Custom"
4. Enter the command: npx homeassistant-mcp
5. Click "Save"

Claude will now use the MCP server for Home Assistant integration, allowing you to control your smart home directly through Claude.

Option 2: Local Installation

1. Update your .env file to enable stdio transport:

   USE_STDIO_TRANSPORT=true
   

2. Run the server using the stdio-start script:

   ./stdio-start.sh
   

   Available options:

   ./stdio-start.sh --debug    # Enable debug mode
   ./stdio-start.sh --rebuild  # Force rebuild
   ./stdio-start.sh --help     # Show help
   

When running in stdio mode:

• The server communicates via stdin/stdout using JSON-RPC 2.0 format
• No HTTP server is started
• Console logging is disabled to avoid polluting the stdio stream
• All logs are written to the log files in the logs/ directory

JSON-RPC 2.0 Message Format

Request Format

{
  "jsonrpc": "2.0",
  "id": "unique-request-id",
  "method": "tool-name",
  "params": {
    "param1": "value1",
    "param2": "value2"
  }
}

Response Format

{
  "jsonrpc": "2.0",
  "id": "unique-request-id",
  "result": {
    // Tool-specific result data
  }
}

Error Response Format

{
  "jsonrpc": "2.0",
  "id": "unique-request-id",
  "error": {
    "code": -32000,
    "message": "Error message",
    "data": {} // Optional error details
  }
}

Notification Format (Server to Client)

{
  "jsonrpc": "2.0",
  "method": "notification-type",
  "params": {
    // Notification data
  }
}

Supported Error Codes

| Code | Description | Meaning | |---------|--------------------|------------------------------------------| | -32700 | Parse error | Invalid JSON was received | | -32600 | Invalid request | JSON is not a valid request object | | -32601 | Method not found | Method does not exist or is unavailable | | -32602 | Invalid params | Invalid method parameters | | -32603 | Internal error | Internal JSON-RPC error | | -32000 | Tool execution | Error executing the tool | | -32001 | Validation error | Parameter validation failed |

Integrating with Claude Desktop

To use this MCP server with Claude Desktop:

1. Create or edit your Claude Desktop configuration:

   # On macOS
   nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
   
   # On Linux
   nano ~/.config/Claude/claude_desktop_config.json
   
   # On Windows
   notepad %APPDATA%\Claude\claude_desktop_config.json
   

2. Add the MCP server configuration:

   {
     "mcpServers": {
       "homeassistant-mcp": {
         "command": "npx",
         "args": ["homeassistant-mcp"],
         "env": {
           "HASS_TOKEN": "your_home_assistant_token_here",
           "HASS_HOST": "http://your_home_assistant_host:8123"
         }
       }
     }
   }
   

3. Restart Claude Desktop.

4. In Claude, you can now use the Home Assistant MCP tools.

JSON-RPC 2.0 Message Format

Usage

Using NPX (Easiest)

The simplest way to use the Home Assistant MCP server is through NPX:

# Start the server in stdio mode
npx homeassistant-mcp

This will automatically:

1. Start the server in stdio mode
2. Output JSON-RPC messages to stdout
3. Send log messages to stderr
4. Create a logs directory if it doesn't exist

You can redirect stderr to hide logs and only see the JSON-RPC output:

npx homeassistant-mcp 2>/dev/null

Manual Installation

If you prefer to install the package globally or locally:

# Install globally
npm install -g homeassistant-mcp

# Then run
homeassistant-mcp

Or install locally:

# Install locally
npm install homeassistant-mcp

# Then run using npx
npx homeassistant-mcp

Advanced Usage