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Mcp Mianshiya Server

mcp-yuyuanweb-mcp-mianshiya-server · by yuyuanweb

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

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Install

$ agentstack add mcp-yuyuanweb-mcp-mianshiya-server

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming — see below.

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About

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

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


#### 构建

``` bash
cd mcp-mianshiya-server
mvn clean package
使用

1) 打开Cherry Studio设置,点击MCP 服务器

2) 点击编辑 JSON,将以下配置添加到配置文件中。

``` json { "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": {} } } }


3) 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。
   
4) 在输入框下面勾选开启MCP服务。
   
5) 配置完成,然后查询下面试题目
   

#### 代码调用

1) 引入依赖

``` java
        
            com.alibaba.cloud.ai
            spring-ai-alibaba-starter
            1.0.0-M6.1
        
    
      org.springframework.ai
      spring-ai-mcp-client-spring-boot-starter
      1.0.0-M6
    

2) 配置MCP服务器 需要在application.yml中配置MCP服务器的一些参数:

``` yaml 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:

``` json
{
  "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:

``` yaml 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](https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key?spm=a2c4g.11186623.0.0.7399482394LUBH) 去申请,模型我们用的是通义千问-Max。
3) 初始化聊天客户端
``` java
@Bean
public ChatClient initChatClient(ChatClient.Builder chatClientBuilder,
                                 ToolCallbackProvider mcpTools) {
    return chatClientBuilder
    .defaultTools(mcpTools)
    .build();
}

4) 接口调用

``` java @PostMapping(value = "/ai/answer/sse", produces = MediaType.TEXTEVENTSTREAM_VALUE) public Flux generateStreamAsString(@RequestBody AskRequest request) {

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

}


## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [yuyuanweb](https://github.com/yuyuanweb)
- **Source:** [yuyuanweb/mcp-mianshiya-server](https://github.com/yuyuanweb/mcp-mianshiya-server)
- **License:** MIT
- **Homepage:** https://www.mianshiya.com

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.