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
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Resume Parser MCPparse this resume text into structured JSON"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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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