mcp-code-sanitizer

<!-- mcp-name: io.github.notasandy/mcp-code-sanitizer -->

mcp-code-sanitizer

Strict AI-powered code reviewer for Claude Desktop, Cursor, VS Code, and Claude Code CLI. Finds bugs, vulnerabilities, and security issues — powered by Groq (free API).

!Python !PyPI !FastMCP !Groq !License

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

!demo

---

Features

| Tool | What it does | |---|---| | analyze_code | Strict review — bugs, security issues, score 0–100 | | compare_code | Compares two versions, detects regressions, recommends merge/request_changes | | explain_code | Step-by-step explanation for junior / middle / senior audience | | generate_tests | Generates pytest / jest / go test — happy path, edge cases, security | | analyze_file | Analyzes a whole file from disk with parallel chunking | | generate_report | Builds an HTML report from any analysis result | | cache_info | Cache statistics and clearing |

Example output

{
  "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"]
}

---

Installation

Prerequisite: Get a free Groq API key at console.groq.com/keys — no credit card required.

Claude Code CLI

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

Claude Desktop

| OS | Config file | |---|---| | macOS | ~/Library/Application Support/Claude/claude_desktop_config.json | | Windows | %APPDATA%\Claude\claude_desktop_config.json | | Linux | ~/.config/Claude/claude_desktop_config.json |

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

Cursor

Create .cursor/mcp.json in your project (or ~/.cursor/mcp.json globally):

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

VS Code

Requires VS Code 1.99+ with GitHub Copilot. Create .vscode/mcp.json in your project:

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

Or add globally via Ctrl+Shift+P → "MCP: Add Server".

Don't have uvx? Install it with pip install uv, then use the commands above.

---

Manual install (alternative)

If you prefer cloning the repo:

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

Then point the client config to: ``json { "command": "python", "args": ["/full/path/to/server.py"], "env": { "GROQ_API_KEY": "gsk_your_key_here" } } ``

---

GitHub Action — automatic PR review

Add AI code review to any repository in 5 lines. The action posts a structured comment on every PR with score, issues, and fix suggestions.

# .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 }}

Add GROQ_API_KEY to your repository secrets → Settings → Secrets → Actions.

The action automatically:

• Reviews only changed files (up to 10 per PR)
• Posts a score and structured issue list as a PR comment
• Fails the check if critical issues are found

---

Usage in chat

After connecting, just write naturally:

Review this code for vulnerabilities:

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

Or call tools explicitly:

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

---

Architecture

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

---

Configuration

All settings via .env or environment variables:

| Variable | Default | Description | |---|---|---| | GROQ_API_KEY | — | Required. Get at console.groq.com | | GROQ_MODEL | llama-3.3-70b-versatile | Groq model to use | | CACHE_TTL | 3600 | Cache TTL in seconds | | CACHE_MAX | 200 | Max cached entries |

Available Groq models

| Model | Speed | Quality | |---|---|---| | llama-3.3-70b-versatile | Fast | Best (default) | | llama-3.1-8b-instant | Fastest | Good | | mixtral-8x7b-32768 | Fast | Great |

---

Contributing

PRs and Issues are welcome. Most wanted:

• Support for other LLM providers (OpenAI, Anthropic)
• New tools: dependency audit, complexity score, docstring generator
• Prompt improvements and new language support

---

License

MIT — do whatever you want. A star would be appreciated.

---

Links

• PyPI
• Groq Console — free API key
• FastMCP docs
• MCP specification
• Smithery
• MCP Registry