Claude / Cursor / VS Code  ──MCP──►  code-sanitizer  ──REST──►  Groq API
                                        (server.py)              (llama-3.3-70b)

{
  "summary": "Critical SQL injection and secret exposed in logs",
  "score": 23,
  "issues": [
    {
      "severity": "critical",
      "line": 2,
      "title": "SQL Injection",
      "description": "f-string directly interpolates user_id into query",
      "fix": "cursor.execute('SELECT * FROM users WHERE id = %s', (user_id,))"
    }
  ],
  "warnings": [{"title": "No exception handling", "description": "..."}],
  "suggestions": ["Consider using an ORM instead of raw SQL"]
}

claude mcp add code-sanitizer -e GROQ_API_KEY=gsk_your_key -- uvx mcp-code-sanitizer

{
  "mcpServers": {
    "code-sanitizer": {
      "command": "uvx",
      "args": ["mcp-code-sanitizer"],
      "env": {
        "GROQ_API_KEY": "gsk_your_key_here"
      }
    }
  }
}

{
  "mcpServers": {
    "code-sanitizer": {
      "command": "uvx",
      "args": ["mcp-code-sanitizer"],
      "env": {
        "GROQ_API_KEY": "gsk_your_key_here"
      }
    }
  }
}

{
  "servers": {
    "code-sanitizer": {
      "command": "uvx",
      "args": ["mcp-code-sanitizer"],
      "env": {
        "GROQ_API_KEY": "gsk_your_key_here"
      }
    }
  }
}

git clone https://github.com/notasandy/mcp-code-sanitizer
cd mcp-code-sanitizer
pip install -r requirements.txt
cp .env.example .env   # add your GROQ_API_KEY
python server.py

{
  "command": "python",
  "args": ["/full/path/to/server.py"],
  "env": { "GROQ_API_KEY": "gsk_your_key_here" }
}

# .github/workflows/ai-review.yml
name: AI Code Review
on:
  pull_request:
    types: [opened, synchronize]

permissions:
  contents: read
  pull-requests: write

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: notasandy/mcp-code-sanitizer@v1
        with:
          groq_api_key: ${{ secrets.GROQ_API_KEY }}

Review this code for vulnerabilities:

def get_user(user_id):
    query = f"SELECT * FROM users WHERE id = {user_id}"
    return db.execute(query)

analyze_file /path/to/my_script.py
generate_tests for this function: ...
compare_code — before vs after refactor, did it get better?
generate_report and save to /tmp/report.html

mcp-code-sanitizer/
├── server.py          # FastMCP entry point
├── config.py          # Constants — keys, limits, extension map
├── groq_client.py     # Async Groq client with auto-retry on 429
├── cache.py           # In-memory LRU cache with TTL
├── prompts.py         # System prompts for all tools
└── tools/
    ├── analyze.py     # analyze_code
    ├── compare.py     # compare_code
    ├── explain.py     # explain_code
    ├── tests.py       # generate_tests
    ├── file_tool.py   # analyze_file — chunking + parallel analysis
    ├── cache_tool.py  # cache_info
    └── report.py      # generate_report — HTML output