dbt MCP Server

The dbt MCP Server is a specialized bridge that equips AI assistants with deep, actionable knowledge about your dbt projects. By exposing the internal state of a dbt Core, dbt Fusion, or dbt Platform instance through the Model Context Protocol, it allows agents to query, modify, and orchestrate data transformations without leaving the conversational interface. This solves a common pain point for data teams: keeping AI tools in sync with complex, version‑controlled ETL pipelines while preserving the safety and reproducibility that dbt enforces.

At its core, the server offers a set of tools that translate dbt concepts into conversational commands. Developers can ask an AI to list models, inspect lineage graphs, run specific transformations, or even modify macro logic. The MCP server handles the translation of natural language into dbt CLI calls, manages authentication and permissions, and returns structured results that the assistant can present in a human‑friendly format. This tight coupling means developers no longer need to switch contexts or manually run commands; the assistant becomes a first‑class interface for data engineering tasks.

Key capabilities include:

• Contextual project insight – Retrieve metadata about models, tests, sources, and snapshots directly from the dbt catalog.
• Execution control – Trigger partial or full runs, target specific models or tags, and monitor job status in real time.
• Version‑aware interactions – Query the current Git state, compare model changes across branches, and suggest refactors.
• Safety mechanisms – Enforce role‑based access so that only authorized commands are executed, protecting production dataflows.

Typical use cases span from onboarding new team members—who can ask the assistant to walk through the pipeline—to day‑to‑day troubleshooting, where a data engineer can request lineage or test results without opening the IDE. In an AI‑driven analytics studio, the server enables conversational data exploration: “Show me all models that depend on ” or “Run the nightly job and alert me when it finishes.”

Integration is straightforward for MCP‑compliant assistants such as Claude or Cursor. The server presents a standard toolset that the assistant can discover and invoke, while developers can extend or customize behavior by adding new tools or prompts. Its open‑source nature invites community contributions, ensuring that the server evolves with dbt’s roadmap and AI’s growing expectations.

Overall, the dbt MCP Server transforms a static data transformation framework into an interactive knowledge base, empowering developers to leverage AI for faster, safer, and more intuitive data engineering workflows.