Resume Analyzer MCP Server 📄🎯

An open-source Model Context Protocol (MCP) server built with Python (mcp SDK) that allows AI models (Claude, Antigravity, Cursor) to analyze resumes, calculate objective ATS (Applicant Tracking System) scores, and suggest job-tailored CV improvements.

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🌟 Features

🛠️ Tools

1. analyze_resume(resume_text: str, target_job_title: str)

   • Evaluates structural completeness (Summary, Experience, Education, Skills, Projects).
   • Detects high-impact action verbs and quantitative performance metrics (e.g. %, $, multipliers).
   • Identifies role-aligned key skills.

2. suggest_improvements(resume_text: str, target_job_title: str)

   • Generates actionable, role-tailored bullet point enhancements.
   • Identifies weak/passive phrasing and recommends high-impact verb upgrades.
   • Applies the Google 'XYZ Formula' (Accomplished X, as measured by Y, by doing Z).

3. calculate_ats_score(resume_text: str, job_description: str)

   • Compares resume text against a target job description.
   • Calculates a precise ATS Match Percentage Score (e.g. ATS Score: 82%).
   • Generates keyword match ratio, matched terms, and critical missing keywords.

📚 Resources

• resume://sample-template: Industry-standard markdown CV template.
• rules://ats-guidelines: ATS parsing standards and bullet-point scoring criteria.

💬 Prompts

• full_resume_review: Pre-built prompt template for running an end-to-end career review workflow.

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💬 Example Prompts for Users & Clients

1. Resume Structural Analysis (analyze_resume)

"Can you use analyze_resume to review my CV below for a Backend Engineer position?"

# John Smith
Skills: Python, PostgreSQL, Docker, REST APIs
Experience: Software Engineer at Acme Inc. Developed backend APIs in Python and reduced database latency by 30%.
Education: B.S. in Computer Science

2. ATS Match Score (calculate_ats_score)

"Please run calculate_ats_score to check my match percentage against this job description."

• Resume: Skills: Python, SQL, PostgreSQL, Docker
• Job Description: Seeking Senior Backend Engineer proficient in Python, SQL, PostgreSQL, Redis, Docker, Kubernetes, CI/CD.

3. Actionable CV Recommendations (suggest_improvements)

"Can you run suggest_improvements on my resume for a Data Engineer role?"

Worked on data pipelines. Helped with SQL queries and handled daily reports.

4. Fetch Resources

"Can you read the resource resume://sample-template to show me a standard resume format?"

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🚀 Quick Start & Local Setup

1. Prerequisites

• Python 3.10 or higher
• Git

2. Installation

Clone or navigate to the project workspace:

cd D:\dev\resume-analyzer-mcp

# Create and activate virtual environment
python -m venv .venv
# On Windows PowerShell:
.\.venv\Scripts\Activate.ps1
# On macOS/Linux:
source .venv/bin/activate

# Install dependencies
pip install -e .

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🧪 Running Local Verification Tests

Run the automated integration test suite which programmatically launches the MCP server via stdio and verifies tool calls, resources, and prompts:

python test_client.py

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🔌 Connecting to MCP Clients

Claude Desktop Configuration

Add the server configuration to your claude_desktop_config.json:

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

{
  "mcpServers": {
    "resume-analyzer": {
      "command": "D:\\dev\\resume-analyzer-mcp\\.venv\\Scripts\\python.exe",
      "args": [
        "D:\\dev\\resume-analyzer-mcp\\server.py"
      ]
    }
  }
}

Antigravity / Gemini Configuration

Add to your workspace .agents/mcp_config.json or ~/.gemini/config/mcp_config.json:

{
  "mcpServers": {
    "resume-analyzer": {
      "command": "python",
      "args": ["D:/dev/resume-analyzer-mcp/server.py"]
    }
  }
}

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☁️ Deploying to Smithery MCP Marketplace

Smithery allows developers to discover, host, and install MCP servers automatically.

Step 1: Push Repository to GitHub

git add .
git commit -m "Add example prompts and documentation"
git remote add origin https://github.com/your-username/resume-analyzer-mcp.git
git push -u origin main

Step 2: Publish to Smithery

1. Visit smithery.ai and sign in with GitHub.
2. Click Submit Server and select your resume-analyzer-mcp repository.
3. Smithery automatically builds your container from smithery.yaml and Dockerfile and renders your README.md with interactive sample prompts!

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📄 License

MIT License. Free for commercial and non-commercial use.