Resume Parser MCP
Uses Google's Gemini AI model to parse unstructured resume text and convert it into structured JSON format with extracted skills, experience, education, and projects
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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 testInstall uv and setup venv use google and install uv setup venv with
python -m venv (name) source (name)/bin/activateInstall dependencies:
uv pip install -r requirements.txtSet up environment variables:
create a new
.envfile and add your API keys:GEMINI_API_KEY= GEMINI_MODEL=gemini-2.0-flash
Run the API locally:
uv run mcp dev main.py
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Maintenance
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