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Augments an LLM with Ontolocy cyber graph capabilities, enabling natural language queries against a Neo4j graph database populated with MITRE ATT\&CK data.
Augments an LLM with Ontolocy cyber graph capabilities, enabling natural language queries against a Neo4j graph database populated with MITRE ATT&CK data.
Simple proof of concept MCP server to augment an LLM with Ontolocy cyber graph capabilities.
Key technologies:
Install dependencies with uv:
uv sync
Make sure you have a .env file which specifies:
FASTMCP_PORT=8008
OPENAI_API_KEY=<YOUR API KEY>
NEO4J_URI="neo4j://localhost:7687"
NEO4J_USERNAME=neo4j
NEO4J_PASSWORD=<YOUR NEO4J PASSWORD>
Ensure your Neo4j database is running and accessible. Be warned, the LLM may run arbitrary queries against it!
Use Ontolocy to populate the graph with MITRE ATT&CK data from the official github repo.
uv run ontolocy parse mitre-attack
uv run server.py
This will make the MCP server available on the port configured in the .env file (e.g.8008).
uv run mcp_sse_client.py lookup mitre attack technique T1090 in the ontolocy cyber graph
Run in your terminal:
claude mcp add ontolocy-mcp-server -- npx Security
Low riskAutomated heuristic from public metadata — not a security guarantee.