Open ontologies: MCP server, setup and security

What Open ontologies does

According to its repository: “Ontology engineering for OWL, RDF and SPARQL: validate, query, diff, lint, version and govern knowledge graphs on an Oxigraph triple store.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Open ontologies is listed under Memory and knowledge, a category of 250 servers in the directory, where it ranks #13 by stars.

Topics declared by the repository: ai-native, description-logics, knowledge-graph, ontology, owl, owl2.

Installing and connecting Open ontologies

No package or remote server is declared in the official MCP registry: you install it from source, following the repository README.

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Rust.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Open ontologies. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on March 9, 2026, the fabio-rovai/open-ontologies repository has 1,333 stars and 185 forks, with 1 open issues. It has more stars than 93% of the servers in the directory. It received changes this month.

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.