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Ontolocy MCP Server

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Ontolocy MCP Server

Simple proof of concept MCP server to augment an LLM with Ontolocy cyber graph capabilities.

Key technologies:

  • Neo4j - for the graph database

  • MCP Python SDK - for the MCP server

  • PydanticAI - for the client (which connects to the MCP server)

  • Neontology - Interacting with Neo4j using pydantic models

  • Ontolocy - Cyber graph ontology and tooling built with Neontology

Quickstart

Pre-Requisites

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!

Populate the Graph

Use Ontolocy to populate the graph with MITRE ATT&CK data from the official github repo.

uv run ontolocy parse mitre-attack

Start the Server

uv run server.py

This will make the MCP server available on the port configured in the .env file (e.g.8008).

Use the CLI Client

uv run mcp_sse_client.py lookup mitre attack technique T1090 in the ontolocy cyber graph

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

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