How to implement an MCP server? What are the best practices?

Implementing an MCP server requires following these steps and best practices:

Step 1: Choose Programming Language and SDK

• MCP supports multiple programming languages: Python, TypeScript/JavaScript, Go, etc.
• Choose from officially provided SDKs or community-maintained implementations
• Python example: Use the mcp package

Step 2: Define Server Configuration

python
from mcp.server import Server
from mcp.types import Tool, Resource

server = Server("my-mcp-server")

Step 3: Register Tools

• Define tool name, description, and parameters
• Implement tool execution logic
• Return structured results

python
@server.tool(
    name="calculate",
    description="Perform mathematical calculations"
)
async def calculate(expression: str) -> str:
    try:
        result = eval(expression)
        return f"Result: {result}"
    except Exception as e:
        return f"Error: {str(e)}"

Step 4: Register Resources (Optional)

• Define accessible resources
• Implement resource read/write logic

python
@server.resource(
    uri="file:///data/config.json",
    name="Configuration File",
    description="Application configuration data"
)
async def get_config() -> str:
    return '{"key": "value"}'

Step 5: Start Server

python
import asyncio

async def main():
    await server.run()

if __name__ == "__main__":
    asyncio.run(main())

Best Practices:

1. Error Handling

   • Catch all exceptions and return friendly error messages
   • Use standard error codes and message formats
   • Log detailed error information

2. Performance Optimization

   • Use async I/O operations
   • Implement caching to reduce redundant calculations
   • Set reasonable timeout values

3. Security

   • Implement input validation and sanitization
   • Limit resource access permissions
   • Use HTTPS for encrypted communication

4. Documentation and Testing

   • Write clear descriptions for each tool
   • Provide usage examples
   • Write unit tests and integration tests

5. Monitoring and Logging

   • Log all requests and responses
   • Monitor server performance metrics
   • Implement health check endpoints

Deployment Considerations:

• Use containerized deployment (Docker)
• Configure load balancing
• Implement auto-restart mechanisms
• Set resource limits

By following these steps and best practices, you can build a stable, efficient, and secure MCP server.