Summary
Two discovery tools so the model stops guessing your schema.
The scope is narrow and stated plainly: an assistant that can list your tables and read their columns writes far fewer invalid queries. Everything past discovery still runs through your own code.
What it is
A server built into the Intugle library. Run intugle-mcp from your project root and it serves your generated semantic model at http://localhost:8080/semantic_layer/mcp over HTTP.
What you get
- get_tables returns every table in the semantic model with the technical description attached to it
- get_schema takes a list of table names and returns their columns, data types and other metadata, including the links between tables
- One URL any MCP client can take — the docs carry ready snippets for Cursor, VS Code, Gemini CLI, JetBrains AI Assistant and Claude Code
Requirements
A semantic model built with SemanticModel and loaded — the discovery tools only appear once one exists. The server runs on your own machine, so the data stays where it already is.
Setup effort
One command plus a key — pip install intugle, then supply credentials