Resume MCP Agent

An intelligent Model Context Protocol (MCP) server for AI-powered resume analysis and sorting. This system helps HR professionals and recruiters efficiently analyze resumes and match them with job descriptions using advanced NLP and machine learning techniques.

Features

• Resume Parsing: Extract text from PDF and DOCX resume files
• Job Description Matching: Intelligent matching between resumes and job requirements
• Skills Analysis: Extract and analyze technical and soft skills
• Experience Evaluation: Assess work experience relevance and seniority
• Education Matching: Evaluate educational background against job requirements
• Scoring System: Comprehensive scoring algorithm for resume ranking
• Web Interface: Modern web UI for easy interaction
• MCP Integration: Full Model Context Protocol support for AI agents

Technology Stack

• Backend: Python with FastAPI
• MCP: Model Context Protocol server implementation
• AI/ML: Google's ADK, spaCy, scikit-learn, transformers
• Document Processing: PyPDF2, python-docx
• Web UI: FastAPI with Jinja2 templates
• Environment: UV for dependency management and virtual environments

Setup

Prerequisites

• Python 3.9 or higher
• UV package manager

Installation

1. Clone the repository:

git clone <repository-url>
cd resume-mcp

2. Create and activate virtual environment with UV:

uv venv
# On Windows
.venv\Scripts\activate
# On Unix/macOS
source .venv/bin/activate

3. Install dependencies:

uv pip install -e .

4. Download spaCy language model:

python -m spacy download en_core_web_sm

5. Set up Google AI credentials (optional):

export GOOGLE_API_KEY="your-api-key"

Usage

Start the MCP Server

resume-mcp

Web Interface

Navigate to http://localhost:8000 to access the web interface.

API Endpoints

• POST /analyze/resume - Analyze a single resume
• POST /match/job - Match resumes with job description
• GET /resumes - List all analyzed resumes
• GET /jobs - List all job descriptions

Project Structure

resume-mcp/
├── src/
│   └── resume_mcp/
│       ├── __init__.py
│       ├── server.py              # MCP server implementation
│       ├── models/                # Data models
│       ├── analyzers/             # Resume and job analysis
│       ├── matching/              # Matching algorithms
│       ├── storage/               # Data storage
│       ├── web/                   # Web interface
│       └── utils/                 # Utility functions
├── templates/                     # HTML templates
├── static/                       # Static assets
├── tests/                        # Test suite
├── pyproject.toml                # Project configuration
└── README.md                     # This file

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

License

MIT License - see LICENSE file for details.