从原理到落地，一文搞懂这个让 AI 模型 “活起来” 的革命性协议！

node -v
npm -v

# 在Windows下
python -m venv venv
venv\Scripts\activate

# 在Linux下
python3 -m venv venv
source venv/bin/activate

pip install mcp[cli] httpx

from textwrap import dedent
import httpx
from typing import Any
import logging

USER_AGENT = "weather-app/1.0"

async def make_nws_request(url: str) -> dict[str, Any] | None:
    """向NWS API发出请求，并进行适当的错误处理。"""
    headers = {
        "User-Agent": USER_AGENT,
        "Accept": "application/geo+json"
    }
    async with httpx.AsyncClient() as client:
        try:
            response = await client.get(url, headers=headers, timeout=30.0)
            response.raise_for_status()
            return response.json()
        except Exception as e:
            logging.error(e)
            return None

from textwrap import dedent
from helpers import make_nws_request, format_alert

NWS_API_BASE = "https://api.weather.gov"

async def get_alerts(state: str) -> str:
    """获取美国某州的天气警报。

    参数:
        state: 两位字母的美国州代码（例如CA, NY）
    """
    url = f"{NWS_API_BASE}/alerts/active/area/{state}"
    data = await make_nws_request(url)
    if not data or "features" not in data:
        return "无法获取警报或没有找到警报。"
    if not data["features"]:
        return "该州目前没有活跃的警报。"
    alerts = [format_alert(feature) for feature in data["features"]]
    return "\n---\n".join(alerts)

from mcp.server.fastmcp import FastMCP

mcp = FastMCP("weather")

@mcp.tool()
async def get_alerts(state: str) -> str:
    # 调用辅助函数获取数据
    pass

@mcp.tool()
async def get_forecast(location: str) -> str:
    # 调用辅助函数获取数据
    pass

if __name__ == "__main__":
    mcp.run(transport='stdio')

uv run weather.py

node --version
npm --version

mkdir pixabay
cd pixabay
npm init -y

npm install @modelcontextprotocol/sdk zod
npm install -D @types/node typescript

{
    "type": "module",
    "bin": {
        "pixabay": "./build/index.js"
    },
    "scripts": {
        "build": "tsc && chmod 755 build/index.js"
    },
    "files": [
        "build"
    ]
}

mkdir src
touch src/index.ts

{
    "compilerOptions": {
        "target": "ES2022",
        "module": "Node16",
        "moduleResolution": "Node16",
        "outDir": "./build",
        "rootDir": "./src",
        "strict": true,
        "esModuleInterop": true,
        "skipLibCheck": true,
        "forceConsistentCasingInFileNames": true
    },
    "include": ["src/**/*"],
    "exclude": ["node_modules"]
}

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const baseUrl = "https://pixabay.com/api/";

const server = new McpServer({ name: "pixabay", version: "1.0.0", capabilities: { resources: {}, tools: {} } });

server.tool('pixabay-image-search', { query: z.string(), type: z.string() }, async ({ query, type = 'all' }) => {
    try {
        if (!process.env.PIXABAY_KEY) {
            console.error("PIXABAY_KEY environment variable is not set");
            process.exit(1);
        }
        const requestUrl = `${baseUrl}?key=${process.env.PIXABAY_KEY}&q=${query}&image_type=${type}&per_page=3`;
        const response = await fetch(requestUrl);
        const json = await response.json();
        return { content: [{ type: 'text', text: JSON.stringify({ images: json.hits || [], total_results: json.total, query }, null, 2) }] };
    } catch (e) {
        // 错误处理
    }
});

const transport = new StdioServerTransport();
server.start(transport);

npm run build

node build/index.js

pip install uvicorn fastapi

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def 首页():
    return { "message": "MCP 太酷了" }

uvicorn main:app --reload

pip install fastapi-mcp

from fastapi import FastAPI
from fastapi_mcp import add_mcp_server

app = FastAPI()
add_mcp_server(app, mount_path = "/mcp", name = "My API MCP")

npm install -g @modelcontextprotocol/server-filesystem

{
    "mcpServers": {
        "mysql": {
            "command": "uv",
            "args": [
                "--directory", 
                "path/to/mysql_mcp_server",
                "run",
                "mysql_mcp_server"
            ],
            "env": {
                "MYSQL_HOST": "localhost",
                "MYSQL_PORT": "3306",
                "MYSQL_USER": "your_username",
                "MYSQL_PASSWORD": "your_password",
                "MYSQL_DATABASE": "your_database"
            }
        }
    }
}

 {
  "mcpServers": {
    "mcp-server-time": {
      "command": "python",
      "args": [
        "-m",
        "mcp_server_time",
        "--local-timezone",
        "Asia/Shanghai"
      ],
      "disabled": false
    }
  }
}