pentestMCP: AI-Powered Penetration Testing via MCP

pentestMCP provides a powerful bridge between Large Language Models (LLMs) and practical penetration testing tools through the Model Context Protocol (MCP). This project functions as an MCP Server, exposing a curated suite of over 20 standard security assessment utilities (Nmap, Nuclei, ZAP, SQLMap, etc.) as callable 'tools'. This allows AI agents within MCP-compatible clients (like Claude Desktop or specific VS Code setups) to leverage these utilities for automated and interactive security analysis tasks.

The goal is to enable natural language control over complex security workflows, making pentesting capabilities more accessible and integrated into AI-driven environments. This work is inspired by Laurie Kirk's GhidraMCP.

Table of Contents

• Core Concepts & Architecture
• Key Features
• Prerequisites
• Installation & Setup
  • Using Pre-built Docker Image (Recommended)
  • Building Docker Image Locally
• Client Host Integration
  • Claude Desktop Integration
  • VS Code Copilot Chat Integration
• Tool Reference
• Security Considerations
• Contributing
• License
• Disclaimer
• Acknowledgements

Video Demo

https://github.com/user-attachments/assets/930c879a-5cb4-478a-b033-f30df0e770a6

Core Concepts & Architecture

pentestMCP strictly adheres to the MCP specification, functioning solely as an MCP Server. It does not embed or directly communicate with any specific LLM. The interaction flow is mediated by an MCP Client Host application:

1. Client Host Application (e.g., Claude Desktop, custom agent): Connects to pentestMCP (typically via stdio brokered by Docker), manages user interaction, and interfaces with a chosen LLM.
2. LLM: Receives user prompts and tool definitions (from pentestMCP via the Client Host). It decides which tools to invoke based on the context.
3. pentestMCP Server (This Project): Runs within a Docker container. Listens for tools/call requests from the Client Host, executes the corresponding underlying tool (e.g., nmap), and returns the results.
4. External Tools: The actual command-line utilities encapsulated within the Docker image.

The server is built using the Python MCP SDK (mcp.server.fastmcp.FastMCP) and features:

• Tool Discovery: Utilizes Python type hints and docstrings for automatic MCP tool schema generation.
• Concurrency Control: A threading.Semaphore limits simultaneous execution of resour

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