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Code Sanitizer MCP Server

by Notasandy
Developer ToolsLow Risk10.0MCP RegistryLocal
Free

Server data from the Official MCP Registry

Strict AI code reviewer powered by Groq. Finds bugs and vulnerabilities.

About

Strict AI code reviewer powered by Groq. Finds bugs and vulnerabilities.

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (0 strong, 3 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.

13 files analyzed Β· 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

Shell Command Execution

Runs commands on your machine. Be cautious β€” only use if you trust this plugin.

What You'll Need

Set these up before or after installing:

Groq API key from console.groq.com/keysRequired

Environment variable: GROQ_API_KEY

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-notasandy-mcp-code-sanitizer": {
      "env": {
        "GROQ_API_KEY": "your-groq-api-key-here"
      },
      "args": [
        "mcp-code-sanitizer"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

πŸ” mcp-code-sanitizer

A strict AI-powered code reviewer that runs your code through Groq LLM directly from Claude Desktop, Cursor, or any MCP-compatible agent.

Python FastMCP Groq License

Claude Desktop  ──MCP──►  code-sanitizer  ──REST──►  Groq API
                            (server.py)               (llama-3.3-70b)

✨ Features

ToolDescription
analyze_codeStrict code review β€” bugs, vulnerabilities, score 0–100
compare_codeCompares two versions, finds regressions, recommends merge/request_changes
explain_codeStep-by-step explanation for junior/middle/senior audience
generate_testsGenerates pytest/jest/go test with happy path, edge cases, security tests
analyze_fileAnalyzes a whole file from disk with parallel chunking
generate_reportBuilds a beautiful HTML report from any analysis result
cache_infoCache statistics and clearing

Example response

{
  "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"]
}

πŸš€ Quick Start

1. Clone the repository

git clone https://github.com/YOUR_USERNAME/mcp-code-sanitizer
cd mcp-code-sanitizer

2. Create virtual environment and install dependencies

python -m venv venv

# macOS / Linux
source venv/bin/activate

# Windows
venv\Scripts\activate

pip install -r requirements.txt

3. Add your Groq API key

Get a free key at console.groq.com/keys

cp .env.example .env
# Open .env and set GROQ_API_KEY=gsk_...

4. Test the server

python server.py

Silence means it's working β€” the server is listening for MCP requests via stdio.


πŸ”Œ Connect to Claude Desktop

Find your config file and add the mcpServers section:

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

Restart Claude Desktop β€” you'll see the πŸ”§ icon in chat.


πŸ”Œ Connect to Cursor

Create .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "code-sanitizer": {
      "command": "/full/path/to/venv/bin/python",
      "args": ["/full/path/to/server.py"],
      "env": {"GROQ_API_KEY": "gsk_your_key_here"}
    }
  }
}

πŸ§ͺ Testing via MCP Inspector

source venv/bin/activate  # or venv\Scripts\activate on Windows
fastmcp dev inspector server.py

A browser UI opens with full tool testing interface.


πŸ’¬ Usage in chat

After connecting to Claude Desktop, just write:

Review this code for vulnerabilities:

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

Or explicitly call a tool:

Use analyze_file on /path/to/my_script.py
Generate tests for this function: ...
Compare these two versions and tell me if it got better: ...

πŸ—οΈ Architecture

mcp-code-sanitizer/
β”œβ”€β”€ server.py          # FastMCP entry point (39 lines)
β”œβ”€β”€ config.py          # Constants β€” keys, limits, mappings
β”œβ”€β”€ groq_client.py     # Groq API client with auto-retry on rate limits
β”œβ”€β”€ cache.py           # In-memory cache with TTL
β”œβ”€β”€ prompts.py         # System prompts for all tools
└── tools/
    β”œβ”€β”€ analyze.py     # analyze_code
    β”œβ”€β”€ compare.py     # compare_code
    β”œβ”€β”€ explain.py     # explain_code
    β”œβ”€β”€ tests.py       # generate_tests
    β”œβ”€β”€ file_tool.py   # analyze_file (chunking + parallel analysis)
    β”œβ”€β”€ cache_tool.py  # cache_info
    └── report.py      # generate_report (HTML)

βš™οΈ Configuration

All settings via environment variables or .env:

VariableDefaultDescription
GROQ_API_KEYβ€”Required. Get at console.groq.com
GROQ_MODELllama-3.3-70b-versatileGroq model
CACHE_TTL3600Cache TTL in seconds
CACHE_MAX200Max cache entries

Available Groq models

ModelSpeedQuality
llama-3.3-70b-versatile⚑⚑⭐⭐⭐⭐⭐ (default)
llama-3.1-8b-instant⚑⚑⚑⭐⭐⭐
mixtral-8x7b-32768⚑⚑⭐⭐⭐⭐

πŸ“¦ Requirements

fastmcp>=2.3.0
httpx>=0.27.0
python-dotenv>=1.0.0

🀝 Contributing

PRs and Issues are welcome! Especially interested in:

  • Support for other LLM providers (OpenAI, Anthropic)
  • New tools (security audit, dependency check, complexity analysis)
  • Prompt improvements

πŸ“„ License

MIT β€” do whatever you want. A GitHub star would be appreciated ⭐


πŸ”— Links

  • FastMCP docs
  • Groq Console
  • MCP specification
  • Smithery β€” MCP server catalog

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Links

Source CodePyPI Package

Details

Published May 4, 2026
Version 0.1.0
0 installs
Local Plugin

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