my-awesome-mcp

An awesome MCP generated by AI

Features

• 🚀 Built with FastMCP framework
• 🔄 Supports both stdio and HTTP transports
• 🐳 Docker ready
• 📝 Type hints throughout
• 🧪 Test suite included
• ⚙️ GitHub Actions CI/CD

Installation

1. Clone this repository
2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   pip install -e .
   

Usage

Stdio Transport (for Claude Desktop, etc.)

my_awesome_mcp-mcp --transport stdio

HTTP Transport (for web integration)

my_awesome_mcp-mcp --transport streamable-http --port 8080

Docker

# Build image
docker build -t my-awesome-mcp .

# Run container
docker run -p 8080:8080 my-awesome-mcp

Available Tools

• example_tool: Echo a message back
• get_server_info: Get information about this MCP server

Development

Running Tests

pip install pytest pytest-asyncio
pytest tests/

Adding New Tools

1. Create a new function in my_awesome_mcp/app.py
2. Decorate it with @mcp.tool()
3. Add proper type hints and docstring
4. The tool will automatically be available to MCP clients

Example:

@mcp.tool()
async def my_new_tool(input_text: str) -> Dict[str, Any]:
    """
    Description of what this tool does.
    
    Args:
        input_text: Description of the parameter
    
    Returns:
        Dictionary with the result
    """
    return {"result": f"Processed: {input_text}"}

Configuration

Deployment

Docker Deployment

This project includes a Dockerfile for easy deployment:

docker build -t my-awesome-mcp .
docker run -p 8080:8080 my-awesome-mcp

CI/CD

This project includes GitHub Actions workflows for:

• Running tests on multiple Python versions
• Building and testing Docker images
• Automated deployment (when configured)

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Run the test suite
6. Create a pull request

License

MIT License