pandaow3r/mcp_server_test

🚀 MCP Server Template

✨ Features

• 🎯 Zero-Config Deployment - Ready for Smithery and other MCP platforms
• 🐍 Modern Python - Built with Python 3.11+ and FastMCP
• 🐳 Docker Ready - Containerized for easy deployment
• 🔧 Template Structure - Perfect starting point for your MCP tools
• 📝 Well Documented - Clear examples and best practices
• ⚡ Fast Setup - Get your MCP server running in minutes

🎯 Quick Start

1. Use This Template

Click the "Use this template" button at the top of this repository to create your own MCP server.

2. Clone & Setup

git clone https://github.com/yourusername/your-mcp-server.git
cd your-mcp-server
pip install -r requirements.txt

3. Run Locally

python server.py

4. Test Your Tools

# Your MCP server is now running and ready to accept connections!

📦 What's Included

mcp-template/
├── 🐍 app.py           # Your tool implementations
├── 🚀 server.py        # MCP server configuration
├── 📋 requirements.txt # Python dependencies
├── 🐳 Dockerfile       # Container configuration
├── ⚙️ smithery.yaml    # Smithery deployment config
└── 📖 README.md        # This beautiful documentation

🛠️ Customize Your Tools

Adding New Tools

1. Implement your tool logic in app.py:

def myAwesomeTool(param: str) -> str:
    """Your amazing tool implementation."""
    # Add your logic here
    return f"Processed: {param}"

2. Register it in the MCP server in server.py:

@mcp.tool()
async def my_awesome_tool(param: str) -> str:
    """
    Description of what your tool does.
    """
    result = myAwesomeTool(param)
    return result

Example Tool Structure

The template includes a dummy tool to get you started:

@mcp.tool()
async def dummy_tool(param: str) -> str:
    """
    A sample tool that processes input parameters.
    """
    awesome_response = dummyTool(param)
    return awesome_response

🚀 Deploy

Smithery Deployment

This template is Smithery-ready! The smithery.yaml configuration is already set up:

1. Push your customized code to GitHub
2. Connect your repository to Smithery
3. Deploy with one click! 🎉

Docker Deployment

# Build the container
docker build -t my-mcp-server .

# Run the container
docker run -p 8000:8000 my-mcp-server

Manual Deployment

Deploy to any platform that supports Python applications:

pip install -r requirements.txt
python server.py

🔧 Configuration

Environment Variables

Customize your MCP server behavior:

export MCP_SERVER_NAME="my-awesome-mcp"
export LOG_LEVEL="INFO"

Dependencies

Add your required packages to requirements.txt:

requests>=2.28.0
mcp
your-additional-package>=1.0.0

📚 Examples

HTTP API Tool

def fetchData(url: str) -> dict:
    """Fetch data from an API endpoint."""
    response = requests.get(url)
    return response.json()

@mcp.tool()
async def fetch_api_data(url: str) -> str:
    """Fetch and return data from a URL."""
    data = fetchData(url)
    return json.dumps(data, indent=2)

File Processing Tool

def processFile(content: str) -> str:
    """Process file content."""
    # Your processing logic
    return content.upper()

@mcp.tool()
async def process_text(text: str) -> str:
    """Process and transform text content."""
    return processFile(text)

🤝 Contributing

Found a bug or have a feature request?

1. 🍴 Fork the repository
2. 🌱 Create a feature branch
3. 💻 Make your changes
4. 🧪 Test thoroughly
5. 📝 Submit a pull request

📄 License

This project is licensed under the MIT License - see the file for details.

🌟 Show Your Support

If this template helped you build something awesome, please consider:

• ⭐ Starring this repository - it makes me happy! 😊
• 🐦 Sharing it with other developers
• 🛠️ Contributing improvements back to the community