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项目结构

在这里插入图片描述
前端项目--------->MCP Client----------->MCP Server

server就不过多赘述了，他只是相当于添加了多个的tools

链接前后端

http.createServer创建一个服务器


// ----------------------------------------------------------------
// server.js
import http from "http";
import url from "url";
// ----------------------------------------------------------------  const server = http.createServer(async (req: any, res: any) => {const parsedUrl = url.parse(req.url, true); // 解析 url（含 query 参数）const name = parsedUrl.query.name; // ✅ 获取 ?name=xxx 的值res.setHeader("Access-Control-Allow-Origin", "*"); // 允许跨域res.setHeader("Content-Type", "application/json; charset=utf-8");// 简单路由匹配if (req.method === "GET" && parsedUrl.pathname === "/api/hello") {console.log("收到请求参数 name =", name);const ans = await mcpClient.processQuery(name as string);console.log("AI 回复：", ans);res.end(JSON.stringify({ message: ans }));} else {res.statusCode = 404;res.end(JSON.stringify({ error: "接口未找到" }));}});// ----------------------------------------------------------------// 启动服务器server.listen(3002, () => {console.log("🚀 本地服务器启动成功：http://127.0.0.1:3002");});

如何区分多个Server

通过获取配置的server，来进行循环，解构出来所有的tools并且绑定对应的serverName来区分属于哪个Server

const paths = [{name: "mcp",args: "/Users/v-yangziqi1/Desktop/work/mcpserver/mcp/build/index.js",},{name: "mcp1",args: "/Users/v-yangziqi1/Desktop/work/mcpserver/mcp1/build/index.js",},
];// 初始化mcp server连接async connectToServer(serverScriptPath?: string) {if (!serverScriptPath) return;const res = await Promise.all(paths.map((item, index) => {this.mcpServer.push(new Client({ name: "mcp-client-cli-" + item.name, version: "1.0.0" }));const mcp = this.mcpServer[index]; // 创建 MCP Client 实例// 判断文件类型const state = item.args.endsWith(".py")? process.platform === "win32"? "python": "python3": process.execPath;//  建立mcp传输层const transport = new StdioClientTransport({command: state,args: [item.args],});mcp.connect(transport); // connect 方法用于连接到 MCP Server。// 获取 MCP Server 上的所有工具名称return mcp.listTools();}));const nestedArr = res.map(({ tools }, index) => {return tools.map((item) => ({ ...item, serverName: index })); // serverName是服务器的index所引致});const toolsArr = nestedArr.flat();// console.log("obj", JSON.stringify(toolsArr, null, 2));// 生成工具数组this.tools = toolsArr.map((t) => ({name: t.name, // 工具名称description: t.description || "", // 工具描述parameters: t.inputSchema, // 工具参数定义Schema的格式execute: async (args: any) => {// 执行工具的逻辑const result = await this.mcpServer[t.serverName].callTool({name: t.name,arguments: args,});return result.content as string;},}));console.log("已连接 MCP Server，工具：",this.tools.map((t) => t.name).join(", "));}

完整代码

// mcp-client-cli.ts
import axios from "axios"; // 引入axios用于发送HTTP请求
import readline from "readline/promises"; // 获取用户的输入命令
import dotenv from "dotenv"; // 用于加载环境变量配置文件（.env）
import { Client } from "@modelcontextprotocol/sdk/client/index.js"; // MCP Client 的核心类
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js"; // StdioClientTransport 是 MCP Client 的传输层，// ----------------------------------------------------------------
// server.js
import http from "http";
import url from "url";
// ----------------------------------------------------------------dotenv.config();const QIHOOGPT_KEY = process.env.QIHOOGPT_KEY;
if (!QIHOOGPT_KEY) throw new Error("请在 .env 中配置 QIHOOGPT_KEY");interface ToolCall {id: string;function: {name: string;arguments: string;};
}interface ToolDefinition {name: string;description: string;parameters: Record<string, any>;execute: (args: any) => Promise<string>;
}
const paths = [{name: "mcp",args: "/Users/v-yangziqi1/Desktop/work/mcpserver/mcp/build/index.js",},{name: "mcp1",args: "/Users/v-yangziqi1/Desktop/work/mcpserver/mcp1/build/index.js",},
];
class MCPClient {private model = "360gpt-pro";private tools: ToolDefinition[] = [];private mcpServer: Client[] = [];// 初始化mcp server连接async connectToServer(serverScriptPath?: string) {if (!serverScriptPath) return;const res = await Promise.all(paths.map((item, index) => {this.mcpServer.push(new Client({ name: "mcp-client-cli-" + item.name, version: "1.0.0" }));const mcp = this.mcpServer[index]; // 创建 MCP Client 实例// 判断文件类型const state = item.args.endsWith(".py")? process.platform === "win32"? "python": "python3": process.execPath;//  建立mcp传输层const transport = new StdioClientTransport({command: state,args: [item.args],});mcp.connect(transport); // connect 方法用于连接到 MCP Server。// 获取 MCP Server 上的所有工具名称return mcp.listTools();}));const nestedArr = res.map(({ tools }, index) => {return tools.map((item) => ({ ...item, serverName: index })); // serverName是服务器的index所引致});const toolsArr = nestedArr.flat();// console.log("obj", JSON.stringify(toolsArr, null, 2));// 生成工具数组this.tools = toolsArr.map((t) => ({name: t.name, // 工具名称description: t.description || "", // 工具描述parameters: t.inputSchema, // 工具参数定义Schema的格式execute: async (args: any) => {// 执行工具的逻辑const result = await this.mcpServer[t.serverName].callTool({name: t.name,arguments: args,});return result.content as string;},}));console.log("已连接 MCP Server，工具：",this.tools.map((t) => t.name).join(", "));}// 将工具定义转换为模型可以理解的格式private convertTool(tool: ToolDefinition) {return {type: "function",function: {name: tool.name,description: tool.description,parameters: tool.parameters,},};}// 360模型的方法private async call360GPT(payload: any) {const { data } = await axios.post("https://api.360.cn/v1/chat/completions",{ ...payload, stream: false },{headers: {"Content-Type": "application/json",Authorization: `Bearer ${QIHOOGPT_KEY}`,},});return data;}// 处理用户查询// 该方法会将用户的查询发送到360GPT模型，并处理返回的async processQuery(query: string) {const messages: any[] = [{ role: "user", content: query }];// 发送用户消息和mcp server的tools到360GPT模型const res = await this.call360GPT({model: this.model, // 模型名称messages, // 用户消息tools: this.tools.map((t) => this.convertTool(t)), // 工具列表tool_choice: "auto", // 自动选择工具});const choice = res.choices[0]; // 获取模型返回的第一个选择const toolCalls = choice.message.tool_calls as ToolCall[] | undefined; // 获取工具调用列表console.log(choice);console.log(toolCalls);// 如果有工具调用，则执行工具if (toolCalls?.length) {console.log("工具调用列表：", toolCalls);for (const call of toolCalls) {// 在 tools 数组中查找与调用名称匹配的工具const tool = this.tools.find((t) => t.name === call.function.name);if (!tool) continue; // 如果没有找到对应的工具，跳过const args = JSON.parse(call.function.arguments || "{}"); // 解析工具调用的参数const result = await tool.execute(args); // 执行工具并获取结果messages.push({ role: "user", content: result }); // 将工具结果添加到消息中console.log(messages);// 再次调用360GPT模型，传入更新后的消息进行润色console.log("🤖 正在思考...");const final = await this.call360GPT({ model: this.model, messages });// 如果有工具调用结果，则返回最终的内容return final.choices[0].message.content;}}return choice.message.content;}// 聊天循环方法async chatLoop() {// 创建 readline 接口，用于读取用户输入const rl = readline.createInterface({input: process.stdin,output: process.stdout,});console.log("输入内容，输入 quit 退出：");while (true) {const query = await rl.question("请输入： "); // 提示用户输入查询内容if (query.toLowerCase() === "quit") break;console.log("🤖 正在思考...");const ans = await this.processQuery(query);console.log("\nAI：", ans, "\n");}rl.close();}
}(async () => {const mcpClient = new MCPClient();const scriptArg = process.argv[2];// 初始化if (scriptArg) await mcpClient.connectToServer(scriptArg);// 服务器监听// await mcpClient.chatLoop();// process.exit(0);// ----------------------------------------------------------------// server.js// 创建一个简单的服务器const server = http.createServer(async (req: any, res: any) => {const parsedUrl = url.parse(req.url, true); // 解析 url（含 query 参数）const name = parsedUrl.query.name; // ✅ 获取 ?name=xxx 的值res.setHeader("Access-Control-Allow-Origin", "*"); // 允许跨域res.setHeader("Content-Type", "application/json; charset=utf-8");// 简单路由匹配if (req.method === "GET" && parsedUrl.pathname === "/api/hello") {console.log("收到请求参数 name =", name);const ans = await mcpClient.processQuery(name as string);console.log("AI 回复：", ans);res.end(JSON.stringify({ message: ans }));} else {res.statusCode = 404;res.end(JSON.stringify({ error: "接口未找到" }));}});// ----------------------------------------------------------------// 启动服务器server.listen(3002, () => {console.log("🚀 本地服务器启动成功：http://127.0.0.1:3002");});
})();