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Resume Gap Analyzer

Resume Gap Analyzer MCP Server

An MCP (Model Context Protocol) server that analyzes resumes against job descriptions to identify gaps, missing keywords, and improvement opportunities using OpenAI's GPT-4o-mini.

https://www.youtube.com/watch?v=JnteMtI5nCs

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Features

  • Gap Analysis: Identifies missing skills, experience, certifications, and keywords

  • Prioritized Recommendations: Actionable feedback organized by impact

  • ATS Optimization: Ensures resume compatibility with Applicant Tracking Systems

  • Strength Mapping: Highlights existing qualifications to emphasize

  • Sample Resume Resources: Test with pre-loaded sample resumes

Setup

Prerequisites

Installation

  1. Clone the repository:

git clone <repository-url> cd gapsinmyresume
  1. Create and activate a virtual environment:

python3 -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate
  1. Install dependencies:

pip install -r requirements.txt
  1. Set your OpenAI API key:

# Copy the example env file cp .env.example .env # Edit .env and add your actual API key # OPENAI_API_KEY=sk-your-actual-key-here

Configuration for Claude Desktop

To use this MCP server with Claude Desktop, add it to your config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{ "mcpServers": { "resume-gap-analyzer": { "command": "/absolute/path/to/gapsinmyresume/.venv/bin/python", "args": ["/absolute/path/to/gapsinmyresume/server.py"] } } }

Important: Replace /absolute/path/to/gapsinmyresume with your actual path. Use the .venv/bin/python from the virtual environment you created.

After updating the config, restart Claude Desktop for changes to take effect.

Usage

Option 1: Via Claude Desktop (Recommended)

Once configured, simply ask Claude in the desktop app:

"Analyze my resume at /Users/you/Documents/resume.docx against this job description: [paste full job description here]"

Claude will automatically use the analyze_resume_gaps tool.

Option 2: Direct CLI Testing

Run the included test script to test without Claude Desktop:

# Make sure your .env file has OPENAI_API_KEY set source .venv/bin/activate python test_cli.py

This will analyze the first resume in sample-resumes/ against a sample job description.

Option 3: MCP Server Directly

Start the MCP server (for debugging or integration):

source .venv/bin/activate python server.py

The server runs in stdio mode and accepts MCP protocol messages.

Tool Parameters

analyze_resume_gaps

  • resume_path (string, required): Absolute path to resume file (.docx)

  • job_description (string, required): Full text of the job posting

Example in Claude Desktop:

"Analyze /Users/you/Documents/resume.docx for the Senior Software Engineer role at XYZ Corp. Job description: We are seeking a Senior Software Engineer with 5+ years of experience in Python, AWS, and React..."

Output Format

The tool returns structured JSON with:

{ "overall_match_score": 75, "critical_gaps": [ { "category": "hard_skill", "gap": "AWS certification missing", "importance": "high", "recommendation": "Obtain AWS Solutions Architect certification", "keywords_to_add": ["AWS", "cloud architecture", "EC2"] } ], "missing_keywords": { "technical": ["Kubernetes", "Docker", "CI/CD"], "soft_skills": ["leadership", "mentoring"], "industry_terms": ["agile", "scrum"] }, "experience_analysis": { "required_years": 5, "resume_shows_years": 3, "gap_exists": true, "notes": "Resume shows 3 years but requires 5+" }, "strengths_to_highlight": [ { "strength": "Python expertise", "relevance": "Primary language for the role", "current_prominence": "medium", "recommendation": "Move Python projects to top of experience section" } ], "formatting_suggestions": [ { "issue": "No clear metrics in achievements", "impact": "both", "fix": "Add quantifiable results (e.g., 'Improved performance by 40%')" } ], "content_improvements": [ { "section": "Professional Summary", "current_state": "Generic software engineer summary", "suggested_change": "Emphasize Python, AWS, and senior-level leadership", "example": "Senior Software Engineer with 3+ years specializing in Python-based cloud solutions...", "priority": "high" } ], "quick_wins": [ "Add 'AWS' keyword to technical skills section", "Quantify achievement in Project X with metrics", "Reorder skills to match job description priority" ], "summary": "Strong Python foundation but needs more AWS experience. Highlight existing cloud projects and add relevant certifications. Focus on quantifying achievements." }

Development

# Run the server directly (for testing) python server.py # Format code black server.py prompts.py # Lint code ruff check .

File Structure

gapsinmyresume/ ├── server.py # Main FastMCP server implementation ├── prompts.py # System prompts and Pydantic models ├── test_cli.py # CLI test script ├── sample-resumes/ # Place sample .docx files here ├── sample-job-descriptions/ # Example job descriptions │ └── senior-software-engineer.txt ├── pyproject.toml # Python project configuration ├── requirements.txt # Python dependencies ├── .env.example # Environment variables template ├── .env # Your API keys (git ignored) ├── README.md # This file └── SETUP.md # Additional setup notes

How It Works

  1. Document Parsing: Extracts text from DOCX files using python-docx

  2. LLM Analysis: Sends resume and job description to OpenAI gpt-4o-mini

  3. Structured Output: Uses Pydantic models with OpenAI's structured output API

  4. MCP Integration: FastMCP exposes analysis as a tool callable from Claude Desktop

Tips for Best Results

  • Provide complete job descriptions (not just titles)

  • Ensure resume files are properly formatted .docx files

  • Include both required and preferred qualifications in job description

  • Use the quick wins section for immediate, high-impact changes

  • Place test resumes in sample-resumes/ to use the resource feature

Quick Start Example

After setup, try this:

# 1. Activate virtual environment source .venv/bin/activate # 2. Run the test script (uses sample resume + sample job description) python test_cli.py # 3. Or use with Claude Desktop # Just ask: "Analyze my resume at /path/to/resume.docx against this job description: [paste description]"

Testing with Sample Resumes

  1. Add .docx files to the sample-resumes/ directory

  2. Sample job descriptions are in sample-job-descriptions/

  3. Run python test_cli.py for quick testing

  4. In Claude Desktop, reference your resume files by absolute path

License

MIT

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security - not tested
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license - not found
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quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Analyzes resumes against job descriptions to identify missing skills, keywords, and improvement opportunities using AI. Provides structured feedback including gap analysis, ATS optimization suggestions, and actionable recommendations to improve job application success.

  1. Features
    1. Setup
      1. Prerequisites
      2. Installation
      3. Configuration for Claude Desktop
    2. Usage
      1. Option 1: Via Claude Desktop (Recommended)
      2. Option 2: Direct CLI Testing
      3. Option 3: MCP Server Directly
      4. Tool Parameters
    3. Output Format
      1. Development
        1. File Structure
          1. How It Works
            1. Tips for Best Results
              1. Quick Start Example
                1. Testing with Sample Resumes
                  1. License

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