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interview-intel-mcp

v2.0.3

Published

面经情报 MCP Server — 让 AI 知道哪些要考、哪些高频、追问链怎么走

Readme

面经情报 MCP Server

让你的 AI 助手(Kiro / Claude Desktop / Cursor 等)直接查询 Java 后端面经数据库。

数据来源:16 家大厂的真实面经,覆盖 MySQL、Redis、并发、JVM、Java 基础、Kafka、MQ、Spring 等模块。

快速开始(无需安装,纯 HTTP 接入)

第一步:获取 Token

访问 面经情报站 → 右上角登录 → 个人中心 → 创建 MCP Token

第二步:配置 AI 工具

Kiro (.kiro/settings/mcp.json):

{
  "mcpServers": {
    "interview-intel": {
      "type": "http",
      "url": "https://tiaozi.site/mcp",
      "headers": {
        "Authorization": "Bearer 你的Token"
      },
      "autoApprove": ["stats", "hot_topics", "frequency_rank",
        "follow_up_patterns", "combo_patterns", "trend",
        "round_analysis", "cross_company", "company_profile",
        "experience_analysis", "search_questions", "study_guide"]
    }
  }
}

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "interview-intel": {
      "type": "http",
      "url": "https://tiaozi.site/mcp",
      "headers": {
        "Authorization": "Bearer 你的Token"
      }
    }
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "interview-intel": {
      "type": "http",
      "url": "https://tiaozi.site/mcp",
      "headers": {
        "Authorization": "Bearer 你的Token"
      }
    }
  }
}

就这两步,无需 clone 仓库、无需本地安装任何东西。

可用工具

| 工具 | 说明 | 典型用法 | |------|------|----------| | stats | 数据概览 | "面经数据库有多少题?" | | hot_topics | 高频考点 | "MySQL 哪些知识点最常考?" | | frequency_rank | 知识点频次排名 | "并发模块知识点按频次排序" | | follow_up_patterns | 追问链分析 | "间隙锁面试官通常怎么追问?" | | combo_patterns | 组合拳分析 | "问完线程池接着问什么?" | | trend | 趋势分析 | "MVCC 是越来越热还是降温了?" | | round_analysis | 按面试轮次分析 | "一面和二面考的有什么区别?" | | cross_company | 跨公司高频考点 | "哪些题被 5 家以上公司考过?" | | company_profile | 公司面试风格 | "字节面试偏好考什么?" | | experience_analysis | 按工作年限分析 | "3 年和 5 年经验面的题有什么不同?" | | search_questions | 搜索面经题目 | "搜索 P6 难度的 Redis 场景设计题" | | question_detail | 单题详情 | "看看这道题的完整追问链" | | study_guide | 学习指南 | "我要面阿里,给个学习优先级建议" |

使用示例

直接用自然语言和你的 AI 对话即可:

  • "帮我看看 MySQL 模块哪些是高频考点"
  • "我准备面字节,应该重点准备什么?"
  • "线程池这个知识点,面试官一般怎么追问?"
  • "哪些知识点是所有大厂都会考的必考题?"
  • "给我搜几道 P6 难度的并发场景设计题"

数据说明

  • 数据来自牛客、掘金、小红书等平台的真实面经
  • 覆盖 16 家公司:阿里、字节、美团、拼多多、携程、百度、腾讯等
  • 持续更新中,欢迎反馈