Ransomware MCP Analysis System

You have a Python-based MCP server designed to analyze ransomware threats, powered by an integrated AI assistant and automated workflows. It exposes a powerful set of analysis tools, supports automatic API configuration, and lets you run and test threat analyses end-to-end with n8n workflows for streamlined results.

How to use

Start by ensuring the MCP server is running and your API key is configured. The server exposes a Python-based MCP API, an AI Gemini agent to interpret user questions, and a test workflow to validate end-to-end analyses. To begin, launch the MCP server, provide authentication via the API key, and then interact with the ransomware.live client or your own integration to submit questions and receive analyzed responses.

How to install

Prerequisites you need installed on your system include Python 3.8+ and a working Python package manager.

pip install -r requirements.txt

echo "API_KEY=YOUR_API_KEY" > .env

Start the MCP server using the Python script provided for the main MCP server component.

python mcp_server_ransomware.py

Optional: run automated tests to verify the workflow integration.

./test_n8n_workflow.sh

Configure and use the n8n workflow by importing the file n8n_ransomware_workflow.json, then configure credentials for the Google AI integration, activate the workflow, and test using example inputs found in example_questions.md.

Configuration and usage notes

API keys should be stored in a non-versioned file named .env. Include the variable API_KEY to authorize requests to the MCP server. The example value is a placeholder you should replace with your real key.

The server provides an automated API configured via the .env file and exposes a range of analysis tools through the MCP interface. The Gemini AI agent analyzes user questions, automatically selects appropriate tools, and returns contextually framed responses grounded in ransomware threat data.

Security, troubleshooting and notes

• Keep API keys and other secrets in .env and avoid committing this file to version control. Use restricted access and rotate keys as needed.

• If you encounter issues starting the server, verify that Python 3.8+ is installed, the dependencies from requirements.txt are installed, and that the .env file contains a valid API_KEY value.

• For troubleshooting, check the logs produced by the MCP server and the n8n workflow for any misconfigurations or authentication failures, then adjust the corresponding configuration files or environment variables.