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Devashishpandey1103

MCP-Powered-AI-Job-Recommendation-Engine

by Devashishpandey1103
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基于 MCP 的 AI 职位推荐引擎

一个由 AI 驱动的职位推荐与简历匹配引擎，集成了 Model Context Protocol (MCP)。该系统对外暴露标准化的 MCP 工具，使 AI 智能体和助手（如 Claude、Antigravity 或自定义 LLM）能够无缝查询职位推荐、解析候选人档案、计算语义技能匹配分数，并执行自动化职业匹配。

🌟 核心功能

  • Model Context Protocol (MCP) 服务器： 暴露标准化工具（recommend_jobs、match_skills、parse_resume、filter_jobs_by_location）。

  • 语义技能匹配： 利用 Transformer 嵌入和余弦相似度，将候选人经验与职位描述进行匹配。

  • 候选人技能差距分析： 标注缺失的关键技能，并推荐个性化学习路径。

  • 交互式 UI 仪表盘： 基于 Streamlit 构建，支持候选人档案上传和实时推荐筛选。

Related MCP server: AI Job Intelligence MCP

🚀 技术栈

  • 协议： Model Context Protocol (MCP Python SDK)

  • AI 与 NLP： LangChain、SentenceTransformers、Scikit-Learn、PyTorch

  • API 与前端： FastAPI、Streamlit、Pandas、NumPy

📁 仓库结构

MCP-Powered-AI-Job-Recommendation-Engine/
├── mcp_server/
│   ├── __init__.py
│   ├── server.py              # MCP Server implementation & tool definitions
│   └── tools.py               # Recommendation tool implementations
├── engine/
│   ├── __init__.py
│   ├── resume_parser.py       # Resume skill extraction engine
│   ├── matcher.py             # Semantic similarity & fit score calculator
│   └── job_database.py        # Job listings & metadata store
├── frontend/
│   ├── app.py                 # Streamlit UI dashboard
├── data/                      # Sample resumes & job description datasets
├── notebooks/                 # Experimentation & embedding evaluation
├── tests/                     # Unit test suites for MCP tools & matcher
├── requirements.txt           # Dependency manifest
└── README.md                  # Project documentation

🛠️ 快速开始

1. 克隆仓库

git clone https://github.com/Devashishpandey1103/MCP-Powered-AI-Job-Recommendation-Engine.git
cd MCP-Powered-AI-Job-Recommendation-Engine

2. 设置环境并安装依赖

python -m venv venv
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

pip install -r requirements.txt

3. 运行 MCP 服务器与 Web 应用

# Start the MCP Server (stdio / SSE transport)
python mcp_server/server.py

# Start the Streamlit Dashboard
streamlit run frontend/app.py

作为 Advanced AI Systems & Model Context Protocol Portfolio 的一部分开发。

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