io.github.imouiche/mitre-attack-mcp-server

🛡️ MITRE ATT&CK MCP Server

AI-Native Access to the World's Leading Threat Intelligence Framework

Features • Installation • Quick Start • Tools • Examples • Roadmap

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🎯 Overview

The MITRE ATT&CK MCP Server transforms the world's leading adversary knowledge base into an AI-native interface. Built for the Model Context Protocol, it enables LLMs and agentic systems to:

• 🔍 Query 200+ techniques, 140+ groups, 700+ software entries
• 🧠 Reason over complex threat relationships and TTPs
• 📊 Visualize coverage gaps with ATT&CK Navigator layers
• ⚡ Scale threat intelligence workflows with structured tools

Perfect for: Security teams, threat hunters, detection engineers, AI researchers, and anyone building intelligent security systems.

What is this?

mitre-attack-mcp-server is a self-contained MCP server that provides machine-callable access to the MITRE ATT&CK framework using official STIX data with LLMs friendly structured outputs.

It enables:

• 🤖 LLMs to reason about ATT&CK techniques, groups, software, and mitigations
• 🧠 Agentic workflows to generate threat explanations and coverage maps
• 🔍 Security teams to query ATT&CK relationships programmatically
• 📊 Visualization via ATT&CK Navigator layers

No scraping.
No fragile APIs.
Just official MITRE data, structured and reliable.

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📑 Table of Contents

• Overview
• Key Features
• Installation
• Quick Start
• MCP Registry
• Available Tools
• Example Queries
• ATT&CK Navigator
• Technical Details
• Roadmap & Vision
• Contributing
• License
• About the Author
• Acknowledgments

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✨ Key Features

• ✅ 65+ MCP tools across ATT&CK domains (Enterprise, Mobile, ICS)
• ✅ Automatic STIX download & caching on first run
• ✅ Native ATT&CK Navigator layer generation
• ✅ Designed for LLMs & MCP-compatible clients
• ✅ In-memory caching for instant query responses
• ✅ Type-safe with Pydantic models
• ✅ Clean, production-ready, self-contained server
• ✅ Comprehensive test coverage

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📦 Installation

Via PyPI (recommended) - Python Users

pip install mitre-mcp-server

npm

npm install -g @imouiche/mitre-attack-mcp-server

npx (no installation required)

npx @imouiche/mitre-attack-mcp-server

Via uv (Modern Python)

uv pip install mitre-mcp-server

Local Development

git clone https://github.com/imouiche/complete-mitre-attack-mcp-server.git
cd complete-mitre-attack-mcp-server
npm install

Using uv (Python package manager)

git clone https://github.com/imouiche/complete-mitre-attack-mcp-server.git
cd complete-mitre-attack-mcp-server
uv sync

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⚡ Quick Start

1. Install

pip install mitre-mcp-server

2. Configure Claude Desktop

Add to your claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "mitre-attack": {
      "command": "npx",
      "args": ["-y", "@imouiche/mitre-attack-mcp-server"]
    }
  }
}

3. Restart Claude Desktop

Quit Claude Desktop completely (Cmd+Q on macOS) and reopen it.

4. Start Querying!

Ask Claude:

"What techniques does APT29 use for initial access?"
"Generate an ATT&CK Navigator layer for ransomware groups"
"Show me all Windows persistence techniques"

Data downloads automatically on first run (~59MB, cached at ~/.mitre-mcp-server/data/).

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📦 MCP Registry

This server is officially registered in the Model Context Protocol (MCP) Registry.

Registry ID: io.github.imouiche/mitre-attack-mcp-server

View in Official Registry: https://registry.modelcontextprotocol.io/?q=mitre-attack-mcp-server

Installation Options

Option 1: Direct NPM

npm install -g @imouiche/mitre-attack-mcp-server

Option 2: NPX (no installation)

npx @imouiche/mitre-attack-mcp-server

Option 3: Discover via Registry

1. Visit MCP Registry
2. Search for "mitre-attack"
3. Click the server card for installation instructions

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🛠️ Available Tools

The server exposes 65+ MCP tools covering all major MITRE ATT&CK entities and relationships.

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📊 Infrastructure & Metadata

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🎯 Techniques

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🧑‍💻 Groups (Threat Actors)

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🧪 Software (Malware & Tools)

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📌 Campaigns

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🛡️ Mitigations

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🧭 Tactics, Data Sources & ICS

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💡 Example Queries

Threat Intelligence

"What techniques does APT29 use for initial access?"
"Which groups target financial institutions?"
"Show me all ransomware-related software"
"What are the aliases for the Lazarus Group?"

Detection Engineering

"What data sources detect credential dumping?"
"Generate a coverage map for EDR capabilities"
"List all techniques for Windows privilege escalation"
"What can detect T1055 (Process Injection)?"

Threat Hunting

"What techniques use PowerShell?"
"Show me lateral movement techniques for Linux"
"Which groups use Cobalt Strike?"
"What persistence techniques target macOS?"

Mitigation & Defense

"What mitigations exist for phishing attacks?"
"Show me all mitigations for privilege escalation"
"What techniques does MFA mitigate?"

Compliance & Gap Analysis

"Generate a layer for all techniques our EDR covers"
"Compare APT29 TTPs against our detection capabilities"
"Show unmitigated techniques in our environment"

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📊 ATT&CK Navigator Visualization

The generate_layer tool produces ATT&CK Navigator–compatible JSON.

Usage:

1. Ask Claude to generate a layer:

   "Generate an ATT&CK Navigator layer for all techniques used by APT29"

2. Save the JSON output to a file (e.g., apt29_layer.json)
3. Upload to ATT&CK Navigator
4. Visualize technique coverage, threat actor usage, or mitigation mapping

Real-World Example Using LangGraph

• Threat Investigation:
  Read my Medium blog demonstrating how a multi-agent LangGraph system leverages these tools to perform a real-world threat investigation.
• Live Demo:
  Explore the interactive Gradio 6.2 demo on Hugging Face Spaces.

Example Layer Use Cases:

• Red Team Coverage: Map all techniques used in an exercise
• Detection Gaps: Highlight unmonitored techniques
• Threat Actor Profile: Visualize group TTPs
• Mitigation Coverage: Show what's protected vs. exposed

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🔧 Technical Details

Architecture

• Language: Python 3.12+
• Framework: FastMCP for Model Context Protocol
• Data Library: Official mitreattack-python (v5.3.0+)
• Async/Await: Optimal performance for concurrent queries
• Type Safety: Full Pydantic models for all data structures
• Testing: Comprehensive pytest coverage

Data

• Enterprise ATT&CK: v18.1+ (~50.9MB)
• Mobile ATT&CK: v18.1+ (~4.9MB)
• ICS ATT&CK: v18.1+ (~3.5MB)
• Total: ~59MB cached locally
• Storage: ~/.mitre-mcp-server/data/v{version}/
• Update: Auto-downloads on install, uses cached data on subsequent runs

Performance

• In-memory caching: All domains loaded at startup
• Query speed: Sub-second for most operations
• Graph traversal: Efficient relationship queries
• Concurrent: Handles multiple simultaneous requests

Requirements

• Python: 3.12 or higher
• Node.js: 16+ (for NPM installation)
• Disk Space: ~150MB (includes dependencies + data)
• Memory: ~200MB RAM when running

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🚀 Roadmap & Vision

This project is the first component of a larger vision to build comprehensive agentic security automation by integrating multiple security knowledge bases and frameworks.

Current Status

• ✅ MITRE ATT&CK - Threat intelligence & adversary TTPs (v18.1)

Planned Integrations

• 🔜 CVE/NVD - Vulnerability intelligence and exploit mapping
• 🔜 MITRE D3FEND - Defensive countermeasure knowledge graph
• 🔜 Sigma Rules - Detection rule translation and management
• 🔜 CAPEC - Common Attack Pattern Enumeration
• 🔜 CWE - Software weakness enumeration
• 🔜 Agentic Pentesting - Multi-agent autonomous security testing

Ultimate Goal

Enable AI agents to autonomously:

• 🎯 Map attack surfaces and identify vulnerabilities
• 🛡️ Recommend defensive countermeasures
• 🔍 Generate detection rules and validate coverage
• 🤖 Orchestrate multi-stage security assessments
• 📊 Reason about complete attack-defense lifecycles

Get Involved

We welcome contributions from:

• 🎓 Students working on thesis projects (cybersecurity, AI, agentic systems)
• 🔬 Researchers in AI security, threat intelligence, or agent frameworks
• 💻 Developers passionate about security automation
• 🏢 Organizations interested in research partnerships or commercial applications

Areas of Interest:

• Integrating additional security frameworks (CVE, D3FEND, Sigma)
• Building agentic workflows for pentesting and red teaming
• Developing detection rule generation pipelines
• Creating threat intelligence reasoning systems
• Improving MCP tooling and documentation

📬 Interested? Open an issue, start a discussion, or reach out directly!

Join the Discussion →

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🤝 Contributing

Found a bug? Have a feature request? Want to contribute to the roadmap?

• 🐛 Report Issues
• 💡 Request Features
• 🔧 Submit Pull Requests
• 💬 Start a Discussion

All contributions welcome!

Development Setup

git clone https://github.com/imouiche/complete-mitre-attack-mcp-server.git
cd complete-mitre-attack-mcp-server
uv sync
# uv run pytest (test/ folder not yet released)
uv run python -m mitre_mcp_server.server

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📜 License

Apache License 2.0

See LICENSE for full details.

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👨‍💻 About the Author

Inoussa Mouiche, Ph.D.
AI/ML Researcher | Cybersecurity | Agentic AI Systems | Software Engineering

🎓 University of Windsor - WASP Lab
🔬 Research Focus: Threat Intelligence Automation, Machine Learning, Multi-Agent Security Systems, LLM-Powered Security Operations

📫 Connect

• 🐙 GitHub: @imouiche
• 📧 Email: mouiche@uwindsor.ca
• 💼 LinkedIn: Inoussa Mouiche, Ph.D.
• 📚 Google Scholar: Publications

🎓 Award Nomination

• Gold Medal: The Governor General's Academic Medal

💼 Open to opportunities in:

• AI/ML Engineering & Research
• Cybersecurity & Threat Intelligence
• Agentic AI Development
• Security Automation & Orchestration
• Academic & Industry Collaborations

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🙏 Acknowledgments

• Built on MITRE ATT&CK® - the industry standard for adversary tactics and techniques
• Powered by mitreattack-python - official MITRE library
• Implements Model Context Protocol - Anthropic's standard for AI-tool integration
• Inspired by the amazing MCP developer community including R. Jasper, and more...

MITRE ATT&CK® is a registered trademark of The MITRE Corporation.

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