# OpenAI的格式
{
    "name": "get_weather",
    "description": "获取天气",
    "parameters": {
        "type": "object",
        "properties": {
            "city": {"type": "string"}
        }
    }
}

# Google的格式
{
    "function_declarations": [{
        "name": "get_weather",
        "description": "获取天气",
        "parameters": {...}
    }]
}

# Anthropic的格式
{
    "name": "get_weather",
    "description": "获取天气",
    "input_schema": {
        "type": "object",
        "properties": {
            "city": {"type": "string", "description": "城市名称"}
        }
    }
}

# 资源：是LLM可以读取的数据
# 类似于"文件"，LLM主动请求读取
{
    "type": "resource",
    "name": "user_profile",
    "uri": "file://./user_profile.json",
    "mimeType": "application/json"
}

# 工具：是LLM可以调用的函数
# 类似于"程序"，LLM调用执行
{
    "type": "tool",
    "name": "send_email",
    "description": "发送邮件",
    "inputSchema": {...}
}

# 1. 初始化请求（客户端 → 服务器）
{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "initialize",
    "params": {
        "protocolVersion": "2024-11-05",
        "capabilities": {
            "roots": {"list": True},
            "sampling": {}
        },
        "clientInfo": {
            "name": "claude-desktop",
            "version": "1.0.0"
        }
    }
}

# 2. 初始化响应（服务器 → 客户端）
{
    "jsonrpc": "2.0",
    "id": 1,
    "result": {
        "protocolVersion": "2024-11-05",
        "capabilities": {
            "tools": {"listChanged": True},
            "resources": {"subscribe": True, "listChanged": True}
        },
        "serverInfo": {
            "name": "filesystem-server",
            "version": "1.0.0"
        }
    }
}

# 工具调用请求
{
    "jsonrpc": "2.0",
    "id": 42,
    "method": "tools/call",
    "params": {
        "name": "read_file",
        "arguments": {
            "path": "/Users/demo/readme.md"
        }
    }
}

# 成功响应
{
    "jsonrpc": "2.0",
    "id": 42,
    "result": {
        "content": [
            {
                "type": "text",
                "text": "# Hello World\n\nThis is a sample file."
            }
        ],
        "isError": False
    }
}

# 错误响应
{
    "jsonrpc": "2.0",
    "id": 42,
    "error": {
        "code": -32603,
        "message": "File not found: /Users/demo/readme.md"
    }
}

# 使用FastMCP的简化版本
from mcp.server.fastmcp import FastMCP

# 创建FastMCP实例
mcp = FastMCP("my-demo-server")

@mcp.tool()
def calculate(operation: str, a: float, b: float) -> dict:
    """
    执行数学计算
    
    为什么使用装饰器而不是显式注册？
    装饰器是一种"声明式"编程风格：
    - 优点：代码简洁，意图清晰
    - 缺点：执行顺序依赖装饰器顺序
    
    适用于：简单工具定义
    """
    operations = {
        "add": lambda x, y: x + y,
        "subtract": lambda x, y: x - y,
        "multiply": lambda x, y: x * y,
        "divide": lambda x, y: x / y if y != 0 else "Error: Division by zero"
    }
    
    if operation not in operations:
        return {"error": f"Unknown operation: {operation}"}
    
    result = operations[operation](a, b)
    return {"operation": operation, "a": a, "b": b, "result": result}

@mcp.resource("config://app")
def get_config() -> str:
    """提供应用配置资源"""
    return '{"version": "1.0.0", "theme": "dark"}'

# 运行服务器
if __name__ == "__main__":
    mcp.run()

# 客户端连接示例
import asyncio
from mcp.client import ClientSession
from mcp.client.stdio import stdio_client

async def main():
    async with stdio_client() as (read, write):
        async with ClientSession(read, write) as session:
            # 1. 初始化连接
            # 握手过程让客户端和服务器交换能力信息
            await session.initialize()
            
            # 2. 列出可用工具
            tools = await session.list_tools()
            print("可用工具:", [t.name for t in tools])
            
            # 3. 调用工具
            result = await session.call_tool(
                "read_file",
                arguments={"path": "/tmp/demo.txt"}
            )
            print("文件内容:", result[0].text)

asyncio.run(main())

from mcp.exceptions import MCPError

async def safe_call_tool(session, tool_name: str, arguments: dict):
    """
    带错误处理的工具调用
    
    MCP定义了标准化的错误格式，客户端应该理解这些错误
    """
    try:
        result = await session.call_tool(tool_name, arguments)
        return {"success": True, "result": result}
    except MCPError as e:
        return {
            "success": False,
            "error": "protocol_error",
            "message": str(e)
        }
    except Exception as e:
        return {
            "success": False,
            "error": "internal_error",
            "message": str(e)
        }

// ~/.claude-desktop/mcp.json
{
    "mcpServers": {
        "filesystem": {
            "command": "npx",
            "args": ["-y", "@anthropic/mcp-server-filesystem"],
            "args": ["/Users/username/projects", "/Users/username/documents"]
        },
        "github": {
            "command": "npx",
            "args": ["-y", "@modelcontextprotocol/server-github"],
            "env": {
                "GITHUB_TOKEN": "your-github-pat"
            }
        }
    }
}