MCP Resume & Job Analyzer

A portfolio-ready Model Context Protocol (MCP) project that exposes resume/job-analysis capabilities as tools an AI host can call.

What this project demonstrates

• MCP server development with the current MCP Python SDK v2

• Typed MCP tools and structured outputs

• Resume text/PDF extraction

• Deterministic skill matching and gap analysis

• Job-fit scoring

• Learning-plan generation

• SQLite persistence

• Unit testing

• Docker-ready architecture

Related MCP server: resume-kit MCP Server

Architecture

User / AI Host
      |
      | MCP
      v
+-----------------------------+
| MCP Resume Job Analyzer     |
|                             |
| analyze_resume              |
| match_job                   |
| calculate_match_score       |
| get_learning_plan           |
| save_analysis               |
+-------------+---------------+
              |
       +------+------+
       |             |
   Analyzer      SQLite DB

Project structure

mcp_resume_job_analyzer/
├── src/
│   ├── __init__.py
│   ├── analyzer.py
│   └── server.py
├── data/
│   ├── sample_resume.txt
│   └── sample_job.txt
├── tests/
│   └── test_analyzer.py
├── requirements.txt
├── Dockerfile
├── .dockerignore
├── .gitignore
└── README.md

Setup

Python 3.10+ is required.

Windows

python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt

Linux / macOS

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run the MCP server

python -m src.server

The server uses stdio transport, which is suitable for local MCP hosts.

Test with MCP Inspector

With the MCP CLI installed:

uv run mcp dev src/server.py

Then inspect the exposed tools.

Available MCP tools

analyze_resume

Extracts known skills, education, experience, projects and certifications from supplied resume text.

match_job

Compares a resume against a job description and returns matched skills, missing skills and evidence.

calculate_match_score

Calculates a transparent skill-based match score.

get_learning_plan

Creates a prioritized learning plan from missing skills.

save_analysis

Persists an analysis result into SQLite.

Example tool flow

1. analyze_resume(resume_text)
2. match_job(resume_text, job_description)
3. calculate_match_score(...)
4. get_learning_plan(missing_skills)
5. save_analysis(...)

Example result

{
  "match_score": 72.0,
  "matched_skills": ["Python", "FastAPI", "LLM", "RAG"],
  "missing_skills": ["MCP", "Docker", "Node.js"],
  "recommendations": [
    "Build an MCP server",
    "Learn Docker fundamentals",
    "Learn Node.js basics"
  ]
}

Next phases

• Phase 2: connect an LLM and build an MCP client/agent

• Phase 3: add FastAPI gateway

• Phase 4: Docker Compose

• Phase 5: evaluation and logging

• Phase 6: GitHub polish + demo screenshots

Resume positioning

Suggested project title:

MCP-Based AI Resume & Job Analyzer | Python, MCP, FastAPI, LLM, Docker

Do not claim LLM integration or Docker deployment on the resume until those phases are actually implemented and tested.