MCP server for Umbrix CTI platform - AI-powered threat intelligence
Project description
Umbrix MCP Server
Connect your AI assistant directly to live threat intelligence with smart MCP tools optimized for both large and small AI models.
🚀 Quick Start
1. Get Your API Key
Visit umbrix.dev, sign in, and generate an API key from Account Settings.
2. Install & Configure
Option A: Docker (Recommended)
git clone https://github.com/trvon/umbrix-mcp.git
cd umbrix-mcp
docker build -t umbrix-mcp:latest .
Option B: Python Package
pip install git+https://github.com/trvon/umbrix-mcp.git
3. Configure Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"umbrix": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "UMBRIX_API_KEY",
"-e", "UMBRIX_API_BASE_URL",
"umbrix-mcp:latest"
],
"env": {
"UMBRIX_API_KEY": "your-api-key-here",
"UMBRIX_API_BASE_URL": "https://umbrix.dev/api"
}
}
}
}
Config file locations:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
4. Alternative: Python Installation
If using pip install instead of Docker:
{
"mcpServers": {
"umbrix": {
"command": "python",
"args": ["-m", "umbrix_mcp"],
"env": {
"UMBRIX_API_KEY": "your-api-key-here",
"UMBRIX_API_BASE_URL": "https://umbrix.dev/api"
}
}
}
}
🤖 Smart MCP Tools
Optimized for all AI model sizes - from GPT-4 to smaller local models.
🎯 Tool Selection Assistant (Perfect for Smaller Models)
- get_tool_recommendation - 🆕 Describe what you want to research → Get personalized tool suggestions
- Example:
get_tool_recommendation("I want to research APT29")→ Suggests best tools for that task
- Example:
🔍 Discovery & Exploration (Great Starting Points)
- discover_recent_threats - Start here! Shows latest activity and data overview
- threat_correlation - Search for any threat entities with simple terms
- analyze_indicator - Deep analysis of specific IOCs (IPs, domains, hashes)
💬 Natural Language Queries (Enhanced for Small Models)
- execute_graph_query - 🚀 ENHANCED Smart tool that converts simple patterns to database queries
- New patterns:
"recent threats","APT29","192.168.1.1","ransomware campaigns" - Still supports: Advanced Cypher queries for expert users
- New patterns:
- threat_intel_chat - Natural language Q&A about threats with graph context
🎯 Specific Entity Lookups
- get_threat_actor - Detailed threat actor profiles and attribution
- get_malware_details - Comprehensive malware analysis from graph database
- get_campaign_details - In-depth campaign intelligence from verified data
- get_cve_details - Comprehensive CVE analysis with severity and exploitation status
📊 Advanced Analysis
- timeline_analysis - Temporal patterns and activity analysis
- indicator_reputation - Reputation scoring for IOCs
- network_analysis - Analyze IP ranges and networks
- threat_actor_attribution - Attribute indicators to actors
- ioc_validation - Validate and enrich indicators
🛠️ System & Management
- system_health_check - Verify platform status when other tools fail
- feed_status - Check threat intelligence feed health
- user_quota - Monitor usage limits and access controls
🧠 Model Size Optimization
For Smaller Models (Claude 3 Haiku, Local LLMs):
- Start with
get_tool_recommendation("describe your task") - Use
discover_recent_threatsfor exploration - Try
execute_graph_querywith simple patterns like"recent threats"or"APT29"
For Larger Models (GPT-4, Claude 3.5 Sonnet):
- Full access to advanced Cypher queries in
execute_graph_query - Complex natural language processing in
threat_intel_chat - Multi-step analysis workflows
Development
# Clone repository
git clone https://github.com/umbrix/umbrix-mcp.git
cd umbrix-mcp
# Install dependencies
uv install
# Run tests
uv run pytest
# Build Docker image
docker build -t umbrix-mcp:latest .
# Test the server
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' | \
docker run --rm -i -e UMBRIX_API_KEY=test umbrix-mcp:latest
📄 License
MIT License - see LICENSE file for details.
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