mcp-server

b9122-jl6929/mcp-server

3.2

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An MCP server that transforms your CV into a digital twin, allowing for interactive Q&A based on your CV content.

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CV Digital Twin MCP Server

An MCP server that takes your CV PDF as input and behaves like your digital twin, answering questions about you based on your CV content.

Features

  • Single Tool Interface: One simple chat_with_me tool handles everything
  • Automatic CV Loading: CV is loaded automatically on first use
  • AI-Powered Digital Twin: Uses OpenAI GPT models to answer questions naturally and conversationally
  • Intelligent Q&A: Ask about work experience, skills, education, contact info, and more

Getting Started

Installation

  1. Install dependencies:
pip install -r requirements.txt
  1. Set up your OpenAI API key:
export OPENAI_API_KEY='your-api-key-here'

Or create a .env file:

OPENAI_API_KEY=your-api-key-here

Usage

As an MCP Server

The server provides a single tool:

chat_with_me: Chat with your digital twin based on your CV

  • Parameters:
    • message (required): Your message or question
    • cv_path (optional): Path to your CV PDF file (only needed on first call)
  • Examples:
    • First call: chat_with_me("Tell me about yourself", cv_path="path/to/my_cv.pdf")
    • Subsequent calls: chat_with_me("What is your work experience?")
    • chat_with_me("What are your skills?")
    • chat_with_me("How can I contact you?")
Local Testing

You can also test the server locally:

python cv_digital_twin.py path/to/your_cv.pdf

Example Questions

The digital twin can answer questions like:

  • "What is your work experience?"
  • "What are your skills?"
  • "Tell me about your education"
  • "What technologies do you know?"
  • "How can I contact you?"
  • "Tell me about yourself"

Files

  • cv_digital_twin.py - Main CV Digital Twin MCP server
  • echo.py - Original echo server example (for reference)
  • requirements.txt - Python dependencies

Dependencies

  • fastmcp - FastMCP framework
  • openai - OpenAI API client for AI-powered responses
  • pdfplumber - PDF text extraction (preferred)
  • PyPDF2 - Alternative PDF library (fallback)

Configuration

The server uses OpenAI's GPT models to generate responses.

Default Model

  • Default: gpt-4o-mini (cost-efficient)
  • Can be changed via environment variable: export OPENAI_MODEL="gpt-4o"

Available Models

  • gpt-4o-mini - Fast and cost-efficient (default)
  • gpt-4o - More capable, higher cost
  • gpt-4 - Legacy GPT-4
  • gpt-3.5-turbo - Fast and economical
  • gpt-4-turbo - Enhanced GPT-4

Note: You'll need an OpenAI API key. Get one at https://platform.openai.com/api-keys

Deployment

This repository is ready to be deployed!

  • Create a new FastMCP Cloud account
  • Connect your GitHub account
  • Select Clone our template and a deployment will be created for you!

Learn More

This repository was created from the FastMCP quickstart template and extended with CV Digital Twin functionality.