MCP Server For Garak LLM Vulnerability Scanner

A lightweight MCP (Model Context Protocol) server for Garak.

Example:

https://github.com/user-attachments/assets/f6095d26-2b79-4ef7-a889-fd6be27bbbda

Tools Provided

Overview

Detailed Description

• list_model_types

  • List all available model types that can be used for attacks

  • Returns a list of supported model types (ollama, openai, huggingface, ggml)

• list_models

  • List all available models for a given model type

  • Input parameters:

    • model_type (string, required): The type of model to list (ollama, openai, huggingface, ggml)

  • Returns a list of available models for the specified type

• list_garak_probes

  • List all available Garak attacks/probes

  • Returns a list of available probes/attacks that can be run

• get_report

  • Get the report of the last run

  • Returns the path to the report file

• run_attack

  • Run an attack with the given model and probe

  • Input parameters:

    • model_type (string, required): The type of model to use

    • model_name (string, required): The name of the model to use

    • probe_name (string, required): The name of the attack/probe to use

  • Returns a list of vulnerabilities found

Prerequisites

1. Python 3.11 or higher: This project requires Python 3.11 or newer.

   # Check your Python version python --version

2. Install uv: A fast Python package installer and resolver.

   pip install uv

   Or use Homebrew:

   brew install uv

3. Optional: Ollama: If you want to run attacks on ollama models be sure that the ollama server is running.

Installation

1. Clone this repository:

2. Configure your MCP Host (Claude Desktop ,Cursor, etc):

Tested on:

• Cursor

• Claude Desktop

Future Steps

• Add support for Smithery AI: Docker and config

• Improve Reporting

• Test and validate OpenAI models (GPT-3.5, GPT-4)

• Test and validate HuggingFace models

• Test and validate local GGML models