mcp_server/
├── mcp_server.py         # MCP server main program
├── mcp_client.py         # MCP client test program
├── routers/
│   ├── __init__.py       # Router package initialization
│   └── base_router.py    # Base router implementation
├── requirements.txt      # Project dependencies
└── README.md             # Project documentation

git clone https://github.com/freedanfan/mcp_server.git
cd mcp_server

pip install -r requirements.txt

python mcp_server.py

export MCP_SERVER_HOST=0.0.0.0
export MCP_SERVER_PORT=8000
python mcp_server.py

python mcp_client.py

export MCP_SERVER_URL="http://your-server-address:port"
python mcp_client.py

{
  "jsonrpc": "2.0",
  "id": "request-id",
  "method": "sample",
  "params": {
    "prompt": "Hello, please introduce yourself."
  }
}

{
  "jsonrpc": "2.0",
  "id": "request-id",
  "result": {
    "content": "This is a response to the prompt...",
    "usage": {
      "prompt_tokens": 10,
      "completion_tokens": 50,
      "total_tokens": 60
    }
  }
}

{
  "jsonrpc": "2.0",
  "id": "request-id",
  "method": "shutdown",
  "params": {}
}

{
  "jsonrpc": "2.0",
  "id": "request-id",
  "result": {
    "status": "shutting_down"
  }
}

def handle_new_method(self, params: dict) -> dict:
    """Handle new method"""
    logger.info(f"Received new method request: {params}")
    # Processing logic
    return {"result": "success"}

def _register_methods(self):
    # Register existing methods
    self.router.register_method("initialize", self.handle_initialize)
    self.router.register_method("sample", self.handle_sample)
    self.router.register_method("shutdown", self.handle_shutdown)
    # Register new method
    self.router.register_method("new_method", self.handle_new_method)

async def handle_sample(self, params: dict) -> dict:
    """Handle sampling request"""
    logger.info(f"Received sampling request: {params}")
    
    # Get prompt
    prompt = params.get("prompt", "")
    
    # Call AI model API
    # For example: using OpenAI API
    response = await openai.ChatCompletion.acreate(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}]
    )
    
    content = response.choices[0].message.content
    usage = response.usage
    
    return {
        "content": content,
        "usage": {
            "prompt_tokens": usage.prompt_tokens,
            "completion_tokens": usage.completion_tokens,
            "total_tokens": usage.total_tokens
        }
    }

# Increase log level
export PYTHONPATH=.
python -m logging -v DEBUG -m mcp_server