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面试鸭 MCP Server

Created By
yuyuanweb8 months ago
基于 Spring AI 的面试鸭搜索题目的 MCP Server 服务,快速让 AI 搜索企业面试真题和答案
Content

面试鸭 MCP Server

简介

面试鸭 的题目搜索API现已兼容MCP协议,是国内首家兼容MCP协议的面试刷题网站。关于MCP协议,详见MCP官方文档

依赖MCP Java SDK开发,任意支持MCP协议的智能体助手(如ClaudeCursor以及千帆AppBuilder等)都可以快速接入。

以下会给更出详细的适配说明。

工具列表

题目搜索 questionSearch

  • 将面试题目检索为面试鸭里的题目链接
  • 输入: 题目
  • 输出: [题目](链接)

快速开始

使用面试鸭MCP Server主要通过Java SDK 的形式

Java 接入

前提需要Java 17 运行时环境

安装

git clone https://github.com/yuyuanweb/mcp-mianshiya-server

构建

cd mcp-mianshiya-server
mvn clean package

使用

  1. 打开Cherry Studio设置,点击MCP 服务器cherry1.png

  2. 点击编辑 JSON,将以下配置添加到配置文件中。

{
  "mcpServers": {
    "mianshiyaServer": {
      "command": "java",
      "args": [
        "-Dspring.ai.mcp.server.stdio=true",
        "-Dspring.main.web-application-type=none",
        "-Dlogging.pattern.console=",
        "-jar",
        "/yourPath/mcp-server-0.0.1-SNAPSHOT.jar"
      ],
      "env": {}
    }
  }
}

cherry2.png

  1. 在设置-模型服务里选择一个模型,输入API密钥,选择模型设置,勾选下工具函数调用功能。 cherry3.png
  2. 在输入框下面勾选开启MCP服务。 cherry4.png
  3. 配置完成,然后查询下面试题目 cherry5.png

代码调用

  1. 引入依赖
        <dependency>
            <groupId>com.alibaba.cloud.ai</groupId>
            <artifactId>spring-ai-alibaba-starter</artifactId>
            <version>1.0.0-M6.1</version>
        </dependency>
    <dependency>
      <groupId>org.springframework.ai</groupId>
      <artifactId>spring-ai-mcp-client-spring-boot-starter</artifactId>
      <version>1.0.0-M6</version>
    </dependency>
  1. 配置MCP服务器 需要在application.yml中配置MCP服务器的一些参数:
spring:
  ai:
    mcp:
      client:
        stdio:
          # 指定MCP服务器配置文件
          servers-configuration: classpath:/mcp-servers-config.json
  mandatory-file-encoding: UTF-8

其中mcp-servers-config.json的配置如下:

{
  "mcpServers": {
    "mianshiyaServer": {
      "command": "java",
      "args": [
        "-Dspring.ai.mcp.server.stdio=true",
        "-Dspring.main.web-application-type=none",
        "-Dlogging.pattern.console=",
        "-jar",
        "/Users/gulihua/Documents/mcp-server/target/mcp-server-0.0.1-SNAPSHOT.jar"
      ],
      "env": {}
    }
  }
}

客户端我们使用阿里巴巴的通义千问模型,所以引入spring-ai-alibaba-starter依赖,如果你使用的是其他的模型,也可以使用对应的依赖项,比如openAI引入spring-ai-openai-spring-boot-starter 这个依赖就行了。 配置大模型的密钥等信息:

spring:
  ai:
    dashscope:
      api-key: ${通义千问的key}
      chat:
        options:
          model: qwen-max

通义千问的key可以直接去官网 去申请,模型我们用的是通义千问-Max。 3) 初始化聊天客户端

@Bean
public ChatClient initChatClient(ChatClient.Builder chatClientBuilder,
                                 ToolCallbackProvider mcpTools) {
    return chatClientBuilder
    .defaultTools(mcpTools)
    .build();
}
  1. 接口调用
    @PostMapping(value = "/ai/answer/sse", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
    public Flux<String> generateStreamAsString(@RequestBody AskRequest request) {

        Flux<String> content = chatClient.prompt()
                .user(request.getContent())
                .stream()
                .content();
        return content
                .concatWith(Flux.just("[complete]"));

    }
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