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Mallory Mcp Server
What is Mallory Mcp Server
Mallory-MCP-Server is a backend server designed for managing cybersecurity intelligence operations using the Model Context Protocol (MCP) framework.
Use cases
Use cases include managing cybersecurity intelligence data, integrating with other security tools, and providing a backend for applications that require real-time data processing.
How to use
To use Mallory-MCP-Server, clone the repository, set up a virtual environment, install dependencies, configure the environment variables in a .env file, and run the server using Python or the MCP CLI.
Key features
Key features include support for Python 3.13+, dependency management with uv, pre-commit hooks for code quality, and customizable configuration through environment variables.
Where to use
Mallory-MCP-Server is suitable for cybersecurity operations, intelligence management, and any application requiring robust backend support for data processing and analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mallory Mcp Server
Mallory-MCP-Server is a backend server designed for managing cybersecurity intelligence operations using the Model Context Protocol (MCP) framework.
Use cases
Use cases include managing cybersecurity intelligence data, integrating with other security tools, and providing a backend for applications that require real-time data processing.
How to use
To use Mallory-MCP-Server, clone the repository, set up a virtual environment, install dependencies, configure the environment variables in a .env file, and run the server using Python or the MCP CLI.
Key features
Key features include support for Python 3.13+, dependency management with uv, pre-commit hooks for code quality, and customizable configuration through environment variables.
Where to use
Mallory-MCP-Server is suitable for cybersecurity operations, intelligence management, and any application requiring robust backend support for data processing and analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Mallory MCP Server
Mallory provides a robust source of cyber and threat intelligence. Use this MCP Server to enable your agents with real-time cyber threat intelligence and detailed information about vulnerabilities, threat actors, malware, techniques and other cyber-relevant entities and content.
📋 Prerequisites
- Python 3.13 or higher
- uv for dependency management (recommended)
🚀 Quick Start
Installation
Clone the repository:
git clone https://github.com/malloryai/mallory-mcp-server.git
cd mallory-mcp-server
Set up a virtual environment and install dependencies:
# Using uv (recommended)
uv venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e .
# Or using pip
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -e .
Install Development Dependencies
For development work, install the optional dependencies:
# Using uv
uv pip install -e ".[lint,tools]"
# Or using pip
pip install -e ".[lint,tools]"
Set Up Pre-commit Hooks
This project uses pre-commit hooks to ensure code quality. Install them with:
pre-commit install ./scripts/install-commit-hook.sh
⚙️ Configuration
Create a .env file in the project root with the following variables:
APP_ENV=local MALLORY_API_KEY=your_api_key_here
🏃♂️ Running the Server
Direct Execution
python -m malloryai.mcp.app
or
uv run malloryai/mcp/app.py
Via the Claude Desktop Configuration
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"MalloryAI": {
"command": "/path/to/uv",
"args": [
"run",
"--python",
"/path/to/mcp-server/.venv/bin/python",
"/path/to/mcp-server/malloryai/mcp/app.py"
],
"env": {
"MALLORY_API_KEY": "your_api_key_here"
}
}
}
}
📦 Project Structure
. ├── README.md ├── app.py # Main application entry point ├── malloryai/ # Main package │ ├── __init__.py │ └── mcp/ # MCP subpackage │ ├── __init__.py │ ├── config/ # Configuration modules │ ├── server/ # Server implementation │ ├── tools/ # Tool implementations │ └── utils/ # Utility functions ├── pyproject.toml # Project metadata and dependencies ├── scripts/ # Utility scripts │ └── install-commit-hook.sh
🧪 Development
Code Style
This project uses:
Format your code with:
black . isort . flake8
Commit Message Format
This project follows the conventional commit format. Each commit message should follow this pattern:
<type>[(scope)]: <description>
Where type is one of:
featorfeature: New featurefix,bugfix, orhotfix: Bug fixeschore: Regular maintenance tasksrefactor: Code changes that neither fix bugs nor add featuresdocs: Documentation only changesstyle: Changes that don’t affect the meaning of the codetest: Adding or correcting testsperf: Performance improvementsci: Changes to CI configurationbuild: Changes to build system or dependenciesrevert: Reverting previous commits
Example: feat(server): add new authentication method
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'feat: add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










