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Home Assistant Model Context Protocol (MCP) Server

by jango-blockchained

IoT/Home AutomationHome AssistantAI AssistantSmart HomeAutomationBunTypeScriptJSON-RPC

A standardized protocol for AI assistants to interact with Home Assistant, providing a secure, typed, and extensible interface for controlling smart home devices. It acts as a bridge between AI models and Home Assistant, enabling AI assistants to execute commands, retrieve information, and stream responses.

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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 🏠🤖

License

License

Bun

Bun
TypeScript

TypeScript
smithery badge

smithery badge

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
  1. 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
  1. Configure your settings:
  • Edit .env file with your Home Assistant details
  • Required: Add your HASS_TOKEN (long-lived access token)
  1. 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

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
  1. 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