Telegram Bot MCP

Telegram Bot MCP

Enables AI assistants to send messages and interact with Telegram chats through MCP tools, with support for user management, conversation history, and bot command handling.

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Telegram Bot MCP

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A Telegram bot powered by FastMCP (Model Context Protocol) that enables AI integration and bot functionality. Available in both simple and full-featured variants to suit different use cases.


📦 Smithery Deployment

You can install this MCP server via Smithery:

npx @smithery/cli install @SmartManoj/telegram-bot-mcp --client claude

🚀 Simple Telegram Bot MCP (simple_telegram_bot_mcp.py)

Perfect for basic message sending and simple integrations

✨ Features

  • Minimal Setup: Single file with just message sending functionality
  • FastMCP Server: Exposes send_telegram_message tool via MCP protocol
  • Lightweight: Perfect for basic notification needs and simple integrations
  • Quick Start: Requires only bot token and chat ID to get started
  • Streamable HTTP: Runs on configurable port with streamable HTTP transport

📋 Requirements (Simple Version)

  • Python 3.10+
  • Telegram Bot Token (from @BotFather)
  • Chat ID where messages will be sent

🛠️ Installation (Simple Version)

  1. Clone the repository:

    git clone https://github.com/your-username/telegram-bot-mcp.git
    cd telegram-bot-mcp
    
  2. Install dependencies:

    pip install fastmcp python-dotenv requests
    
  3. Set up environment variables:

    TELEGRAM_BOT_TOKEN=your_bot_token_here
    TELEGRAM_CHAT_ID=your_chat_id_here
    

🚀 Quick Start (Simple Version)

# Run simple MCP server on default port 8001
python simple_telegram_bot_mcp.py

# Run on custom port
python simple_telegram_bot_mcp.py 8002

🔧 MCP Tool (Simple Version)

The simple bot exposes one MCP tool:

  • send_telegram_message(text: str): Send a message to the configured Telegram chat

🐳 Docker Usage (Simple Version)

# Build image
docker build -t simple-telegram-bot-mcp .

# Run container
docker run -e TELEGRAM_BOT_TOKEN=your_token -e TELEGRAM_CHAT_ID=your_chat_id simple-telegram-bot-mcp

🏢 Full-Featured Telegram Bot MCP (telegram_bot_mcp.py)

Complete solution with advanced features and production capabilities

🚀 Features (Full Version)

  • FastMCP Integration: Built with FastMCP framework for seamless AI model integration
  • Multiple Deployment Modes: Supports polling, webhook, and combined modes
  • MCP Tools & Resources: Expose Telegram functionality as MCP tools and resources
  • AI-Powered Responses: Context-aware intelligent responses
  • User Management: Track users, sessions, and conversation history
  • Production Ready: FastAPI webhook server for production deployment
  • Comprehensive Logging: Detailed logging and monitoring capabilities
  • Flexible Configuration: Environment-based configuration management

📋 Requirements (Full Version)

  • Python 3.10+
  • Telegram Bot Token (from @BotFather)
  • Optional: AI API keys (OpenAI, Anthropic) for enhanced features

🛠️ Installation

  1. Clone the repository:

    git clone https://github.com/your-username/telegram-bot-mcp.git
    cd telegram-bot-mcp
    
  2. Install dependencies:

    pip install -r requirements.txt
    
  3. Set up environment variables:

    cp env.example .env
    # Edit .env file with your configuration
    
  4. Configure your bot token:

    • Create a bot with @BotFather
    • Copy the token to your .env file

⚙️ Configuration

Create a .env file based on env.example:

# Required
TELEGRAM_BOT_TOKEN=your_bot_token_here

# Optional - for webhook mode
TELEGRAM_WEBHOOK_URL=https://your-domain.com/webhook

# Server settings
SERVER_HOST=0.0.0.0
SERVER_PORT=8000
MCP_PORT=8001

# Optional - for AI features
OPENAI_API_KEY=your_openai_key_here
ANTHROPIC_API_KEY=your_anthropic_key_here

# Debug settings
DEBUG=false
LOG_LEVEL=INFO

🚀 Quick Start

Method 1: Using the Unified Starter (Recommended)

# Check configuration
python start.py --check-config

# Start in polling mode (default)
python start.py

# Start in webhook mode
python start.py --webhook

# Start MCP server only
python start.py --mcp

# Start both webhook and MCP server
python start.py --combined

Method 2: Individual Components

# Run bot in polling mode
python bot_runner.py

# Run webhook server
python webhook_server.py

# Run MCP server
python telegram_bot_mcp.py --server

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Telegram      │    │   FastAPI        │    │   FastMCP       │
│   Bot API       │◄──►│   Webhook        │◄──►│   Server        │
│                 │    │   Server         │    │                 │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │                         │
                                ▼                         ▼
                       ┌──────────────────┐    ┌─────────────────┐
                       │   Bot Runner     │    │   AI Models     │
                       │   (Handlers)     │    │   (OpenAI, etc) │
                       └──────────────────┘    └─────────────────┘

📂 Project Structure

telegram-bot-mcp/
├── telegram_bot_mcp.py    # Main FastMCP server
├── bot_runner.py          # Telegram bot logic
├── webhook_server.py      # FastAPI webhook server
├── start.py              # Unified startup script
├── config.py             # Configuration management
├── requirements.txt      # Python dependencies
├── env.example          # Environment variables template
├── README.md            # This file
└── .gitattributes       # Git configuration

🔧 MCP Integration

This bot exposes several MCP tools and resources:

Tools

  • send_telegram_message: Send messages to Telegram chats
  • get_chat_info: Get information about Telegram chats
  • broadcast_message: Send messages to all known users
  • get_bot_info: Get bot information and capabilities

Resources

  • telegram://messages/recent/{limit}: Get recent messages
  • telegram://users/active: Get list of active users
  • telegram://stats/summary: Get bot statistics

Prompts

  • create_welcome_message: Generate welcome messages
  • generate_help_content: Create help documentation

🤖 Bot Commands

  • /start - Initialize bot and show welcome message
  • /help - Display help information
  • /info - Show user profile and session info
  • /stats - View bot statistics
  • /clear - Clear conversation history

🌐 Deployment

Development (Polling Mode)

python start.py --polling --debug

Production (Webhook Mode)

  1. Set up your domain and SSL certificate
  2. Configure webhook URL:
    export TELEGRAM_WEBHOOK_URL=https://your-domain.com/webhook
    
  3. Start the server:
    python start.py --webhook
    

Docker Deployment (Optional)

Create a Dockerfile:

FROM python:3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .

CMD ["python", "start.py", "--webhook"]

Required configuration:

  • telegramBotToken: Your Telegram Bot API token from @BotFather
  • telegramChatId: The chat ID where messages will be sent

🔍 API Endpoints

When running in webhook mode, the following endpoints are available:

  • GET / - Server information
  • GET /health - Health check
  • POST /webhook - Telegram webhook
  • GET /bot/info - Bot information
  • GET /mcp/status - MCP server status
  • GET /stats - Server statistics

📊 Monitoring

The bot provides comprehensive logging and monitoring:

  • Health checks: /health endpoint
  • Statistics: User activity, message counts, command usage
  • Logging: Structured logging with configurable levels
  • Error tracking: Detailed error reporting

🛡️ Security

  • Webhook verification: Optional signature verification
  • Environment variables: Secure configuration management
  • Input validation: Pydantic models for data validation
  • Error handling: Graceful error handling and logging

🔧 Customization

Adding New Commands

Edit bot_runner.py and add new command handlers:

@self.application.add_handler(CommandHandler("mycommand", self.my_command))

async def my_command(self, update: Update, context: CallbackContext):
    await update.message.reply_text("Hello from my command!")

Adding MCP Tools

Edit telegram_bot_mcp.py and add new tools:

@mcp.tool()
async def my_tool(param: str, ctx: Context) -> str:
    """My custom tool"""
    return f"Processed: {param}"

Custom AI Integration

The bot can be integrated with various AI models through the MCP protocol. Add your AI processing logic in the _process_with_mcp method.

🐛 Troubleshooting

Common Issues

  1. Bot token not working:

    • Verify token with @BotFather
    • Check .env file configuration
  2. Webhook not receiving updates:

    • Verify webhook URL is accessible
    • Check SSL certificate
    • Review server logs
  3. MCP server connection issues:

    • Ensure MCP server is running
    • Check port configuration
    • Verify firewall settings

Debug Mode

Enable debug mode for detailed logging:

python start.py --debug --log-level DEBUG

📝 Logging

Logs are structured and include:

  • Timestamp
  • Log level
  • Component name
  • Message details

Configure logging level via environment variable:

LOG_LEVEL=DEBUG  # DEBUG, INFO, WARNING, ERROR

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new functionality
  4. Submit a pull request

📜 License

This project is licensed under the MIT License. See LICENSE file for details.

🙏 Acknowledgments


Built with ❤️ using FastMCP and Python

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