AI assistants are becoming part of every engineering team. The question is what they are grounded in. The OML MCP server makes your formal engineering knowledge available to them as first-class tools, using the open Model Context Protocol.

Through MCP, an AI assistant can read and update your models, run the reasoner, execute queries over asserted and entailed knowledge, and follow your methodology, all with the same rigor as a human user of the platform. The assistant proposes; the formal semantics verify. That combination is what keeps AI output trustworthy enough for engineering work.

Because MCP is an open standard, you are not locked into one assistant. The tools work with the AI your organization already uses, in chat sessions, in agentic workflows, and in automation that chains modeling steps together.

What you get

• Modeling, reasoning, and querying exposed as standard MCP tools
• AI agents that act on your models with methodology compliance and reasoner verification
• Compatibility with any MCP-capable assistant, proprietary or open source
• A foundation for agentic engineering workflows that go beyond chat

If you are exploring how AI agents fit into your engineering process, this is the piece that makes them trustworthy. We are happy to demonstrate an agent working a real model.