MCP is currently under active development and in alpha stage. We're looking for contributors to help build out this exciting project! Whether you're interested in:
- Implementing new tool integrations
- Improving the AI assistant's capabilities
- Enhancing the UI/UX
- Writing documentation
- Testing the system
Your contributions are welcome! See CONTRIBUTING.md for how to get started.
The Model Context Provider (MCP) is an open-source framework that bridges AI with penetration testing tools. MCP interfaces with a wide array of pentesting tools, parses and enriches their output in real-time, and strictly follows the standard penetration testing process. It guides human pentesters through each phase – from reconnaissance and scanning to exploitation, post-exploitation, and reporting – aligning with established methodologies.
⚠️ Disclaimer: This tool is intended for legal security testing with proper authorization. Misuse of this software for unauthorized access to systems is illegal and unethical.
- Methodology Enforcement: Ensures each engagement progresses through proper phases (reconnaissance → scanning → exploitation → post-exploitation → reporting) in order.
- Real-time Context Aggregation: Captures tool outputs, normalizes the data into a unified engagement context, and stores it for analysis.
- LLM-Powered Insights: Leverages a large language model to interpret findings and provide guidance during the engagement.
- Seamless Tool Integration: Acts as a middleware layer that hooks into major pentest tools, converting their results into a common event format.
- Secure Data Handling: Enforces strict security on processed data, including sanitization when interacting with the LLM.
- Reporting and Knowledge Retention: Logs all findings and actions in a structured format for report generation.
MCP is built on a microservices-based, event-driven system deployed in a containerized environment:
- Core Context Processing Engine: Central brain that aggregates and normalizes data from all tools
- AI-Powered Attack Path Analyzer: Identifies potential attack paths and prioritizes targets
- Plugin-Based Integration Framework: Extensible system for interfacing with external tools
- Secure Logging & Reporting Module: Maintains engagement logs and produces reports
- Real-Time LLM Query Interface: Provides natural language interface for querying findings
- Role-Based Access Control: Enforces security across all operations
MCP currently integrates with the following tools:
- Metasploit Framework: Exploitation framework
- Hydra: Network login brute-force tool
- John the Ripper: Offline password cracker
- LinPEAS: Linux Privilege Escalation enumeration script
- Python 3.8+
- Nmap (for network scanning)
- Gobuster (for web enumeration)
- Proper authorizations and scope definitions for penetration testing
- Clone this repository:
git clone https://github.com/allsmog/mcp-pentest.git
cd mcp-pentest- Install the MCP server:
pip install -e .- Install required dependencies:
pip install mcp- Add this MCP server to your Claude Desktop configuration. Edit your
claude_desktop_config.json:
{
"mcpServers": {
"mcp-pentest": {
"command": "python",
"args": ["/path/to/mcp-pentest/server.py"],
"env": {}
}
}
}-
Restart Claude Desktop
-
You should now see the penetration testing tools available in Claude Desktop. Try commands like:
- "Run an nmap scan on 127.0.0.1"
- "Perform a gobuster directory scan on https://httpbin.org"
- "Show me the latest scan events"
You can also test the server directly:
# Run the MCP server
python server.py
# The server will communicate via stdio using the MCP protocolSee our documentation for complete API references and examples.
Here's what we're currently working on:
- Completing core Context Engine implementation
- Finishing initial tool integrations
- Building the AI-powered attack path analyzer
- Developing the web UI
- Creating comprehensive test suite
- Adding additional tool integrations
- Implementing report generation
We welcome contributions to any of these areas!
Contributions are welcome and appreciated! Please see CONTRIBUTING.md for guidelines.
We're particularly looking for help with:
- Tool Integrations: Adding support for more security tools
- Testing: Real-world testing and bug reporting
- Documentation: Improving and expanding guides
- UI Development: Building the web interface
- AI Components: Enhancing LLM integration and attack path analysis
We especially welcome contributions for new tool integrations. See our Tool Integration Guide for how to add support for additional tools.
- Issues: Use GitHub issues for bug reports and feature requests
- Discussions: GitHub discussions for general questions and ideas
This project is licensed under the MIT License - see the LICENSE file for details.
Given the nature of this tool, please be especially mindful of security:
- Never commit credentials, API keys, or sensitive information
- Always follow responsible disclosure practices
- Ensure proper authorization before testing any systems
- Thanks to all the open-source penetration testing tools this project builds upon
- Special recognition to the security researchers and tool developers who inspire this work

