
mallory mcp server
Mallory - Cyber Threat Intelligence MCP Server
Repository Info
About This Server
Mallory - Cyber Threat Intelligence MCP Server
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
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:
- Black for code formatting
- isort for import sorting
- flake8 for linting
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
Quick Start
Clone the repository
git clone https://github.com/malloryai/mallory-mcp-serverInstall dependencies
cd mallory-mcp-server
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
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