MalloryAI MCP Server
by malloryai
The MalloryAI Intelligence MCP Server provides a robust backend for managing cybersecurity intelligence operations through the MCP (Model Context Protocol) framework. It's designed to facilitate and streamline cybersecurity intelligence workflows.
Last updated: N/A
What is MalloryAI MCP Server?
The MalloryAI MCP Server is a backend application designed to manage cybersecurity intelligence operations using the Model Context Protocol (MCP). It provides a structured environment for handling and processing intelligence data.
How to use MalloryAI MCP Server?
To use the server, clone the repository, set up a virtual environment with Python 3.13 or higher, install dependencies using uv or pip, configure environment variables (specifically the MALLORY_API_KEY), and run the server using the provided commands. It can also be integrated with the Claude Desktop Configuration.
Key features of MalloryAI MCP Server
MCP framework integration
Dependency management with uv (recommended)
Pre-commit hooks for code quality
Configurable environment variables
Modular project structure
Adherence to conventional commit format
Use cases of MalloryAI MCP Server
Managing cybersecurity intelligence data
Automating intelligence workflows
Integrating with other cybersecurity tools
Developing cybersecurity applications
Researching cybersecurity threats
FAQ from MalloryAI MCP Server
What is MCP?
What is MCP?
MCP stands for Model Context Protocol, a framework for managing cybersecurity intelligence operations.
What Python version is required?
What Python version is required?
Python 3.13 or higher is required.
How do I install dependencies?
How do I install dependencies?
You can use uv (recommended) or pip to install the necessary dependencies.
What is the purpose of the .env file?
What is the purpose of the .env file?
The .env file is used to store environment-specific configuration variables, such as API keys.
How do I contribute to the project?
How do I contribute to the project?
Fork the repository, create a feature branch, commit your changes, push to the branch, and open a Pull Request.