Resume Parser MCP

Resume Parser MCP

Enables parsing of raw resume text into structured JSON format with organized sections for skills, experience, education, and projects. Uses Google's Gemini AI model to extract and categorize resume information from unstructured text input.

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Json to Json Resume-Parser MCP

This is a resume parser MCP that takes a random json input: { "raw_text": "John Doe, Software Engineer with 3 years of experience in Python, AWS, Docker. Worked at Acme Inc from 2020 to 2023..." } Into a more sturctured output: { "skills": ["Python", "AWS", "Docker"], "experience": [ {"company": "Acme Inc", "role": "Software Engineer", "years": "2020-2023"} ], "education": [], "projects": [] } using gemini model..

Clone the repository:

git clone https://github.com/Acidlambunk/Resume-Parser-MCP.git
cd test

  1. Install uv and setup venv use google and install uv setup venv with

    python -m venv (name)
source (name)/bin/activate

  2. Install dependencies:

    uv pip install -r requirements.txt

  3. Set up environment variables:

  • create a new .env file and add your API keys:
    GEMINI_API_KEY=
GEMINI_MODEL=gemini-2.0-flash
  1. Run the API locally:
    uv run mcp dev main.py

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