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dbt MCP

Explore dbt models, lineage and test results from an AI agent.

DatabaseFreeClaudeClaude CodeCursorVS CodeAll ModelsModerate✓ Verified
Visit Tool608 stars

Last verified: September 20, 2026

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Active
Last code update: September 25, 2026License: Apache-2.0Checked September 28, 2026

How to Install dbt MCP

$uvx dbt-mcp

Requires Claude Desktop, Cursor, Windsurf, or another MCP-compatible client.

Setup by client

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "dbt-mcp": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "dbt-mcp": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ]
    }
  }
}

VS Code (.vscode/mcp.json)

{
  "servers": {
    "dbt-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ]
    }
  }
}

Claude Code (terminal)

claude mcp add dbt-mcp -- uvx dbt-mcp

Add any API keys or environment variables the server's README lists.

About dbt MCP

dbt's MCP server gives an agent access to the semantic layer, model definitions, lineage graph and test results in a dbt project. That turns questions like "what feeds this table and did its tests pass" into a single prompt instead of a manual trawl through the DAG. It is particularly effective during incident response, when tracing a bad number back through transformations is the slow part. Downstream, you can connect Tableau to Claude to query the dashboards built on those models.

dbt MCP is a Database MCP server designed for developers, analysts, and data teams. It enables querying and managing databases from an AI assistant by exposing schema introspection and SQL execution as MCP tools. Key capabilities include schema introspection across tables and views, parameterised sql execution, read-only and read/write modes, and structured tool calls that work cleanly inside an LLM context. It integrates with Postgres, MySQL, SQLite, MongoDB, Redis, BigQuery, and Snowflake, and is best suited for developers, analysts, and data teams who need ad-hoc analytics without a bi tool.

Key Features

  • dbt
  • semantic-layer
  • lineage
  • analytics-engineering
  • data-quality

Pricing

Free: from Free (dbt project required; Cloud features need a dbt Cloud account)

Pros & Cons

Pros

  • Lets the assistant write and run real queries instead of guessing
  • Read-only mode is safe to point at production-shaped data
  • Skips most ORM and CSV-shuffling boilerplate

Cons

  • Misconfigured permissions can expose sensitive data
  • Long-running queries need explicit timeouts
  • Schema drift requires reconnecting or refreshing context

Best For

  • Ad-hoc analytics without a BI tool
  • Drafting migrations and reviewing query plans
  • Letting non-SQL teammates ask questions of a database
  • Bootstrapping internal admin workflows

Our Take on dbt MCP

Excellent for tracing lineage and test failures conversationally. Assumes a mature dbt project: thin value if your transformations live elsewhere.

Frequently Asked Questions

Tags

#Database#dbt#semantic-layer#lineage#analytics-engineering#data-quality