Natural-language SQL breaks quietly when schema context goes stale.
The model may still produce SQL that looks reasonable.
The query may even run.
But if a column was renamed, a relationship changed, a view gained new filtering logic, or a metric moved to an approved surface, the answer can be wrong in a way that is hard to spot.
For MCP database servers, schema drift detection should be part of the tool contract.
Practical things I would want in production:
- schema/context version on every tool result
- metadata refresh timestamp
- migration/catalog hash where possible
- detection for changed tables/views/columns
- refusal when context is stale
- audit trail tying query output to the context used
Longer version: Schema drift detection for MCP database servers
The model cannot safely reason from yesterday's database shape.