Snowflake

You have a Snowflake schema and about thirty minutes. By the end of this tutorial you will have a governed model of that schema in CoreModels - tables as Types, columns as Elements with their native types preserved, declared keys as checks and references, object dependencies as lineage - and you will have run your first drift audit against it and read the result.

This is the reference walk through everything you can do with the Snowflake integration over plain HTTP - every route, its role requirement, its request body, and what comes back. The Snowflake connector declares all three capabilities - Import, Audit, and Generate - so every verb below is live for it.

"Is our Snowflake estate still in sync with the governed model? If not, show me exactly what drifted, and draft the DDL to fix it." That is a sentence you can now say to an AI agent, and every step it takes to answer - discovery, audit, report, generation - runs through the CoreModels MCP server as first-class tool calls. This article walks the whole flow: how an agent connects, which integration tools it gets, the exact arguments each takes, and how large metadata extracts travel via the `artifactUrls` path.

Schema drift has two directions, and most teams only guard one. The warehouse can move away from the agreed model - a column retyped in a Friday migration, a table quietly dropped. But the model can also move away from the warehouse - someone tightens an allowed-value list in governance and nobody re-checks the estate. This article wires up automation for both directions against a Snowflake estate governed in CoreModels: a CI gate on the machine-to-machine API, a status badge, the rolling audit history, one-call re-audits, and the scheduled heartbeat that keeps the loop honest between changes.

Take one column - `ORDER_TOTAL NUMBER(38,2)` in `ANALYTICS.PUBLIC.ORDERS` - and follow it from an `INFORMATION_SCHEMA` row to a governed graph node. That single trace touches everything interesting about the Snowflake connector in CoreModels: how identity is minted, how native types map (and where they approximate), what rides the vendor-metadata mixin, how keys and dependencies become checks and lineage, which audit rules are Snowflake's own, and where the connector honestly declines to guess. This article is that trace, written for people who want to know exactly what the import does before pointing it at production metadata.