AI-driven MCP server that audits, profiles, detects schema drift, and auto-generates documentation for dbt projects, enabling natural language interaction with your dbt project's health.
A read-only MCP server that exposes dbt project artifacts and data quality result tables (BigQuery/Postgres) to LLM clients, enabling deep introspection, run-history analysis, source freshness, test coverage, and lineage walks.
A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.