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Searchable catalog of Model Context Protocol servers. Find tools that connect your AI assistant to the services and data you use.

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Data PlatformsOfficialPython
D

dbt-labs/dbt-mcp

Official MCP server for dbt (data build tool) providing integration with dbt Core/Cloud CLI, project metadata discovery, model information, and semantic layer querying capabilities.

0 starsUpdated Sep 2, 2026
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Overview

Official MCP server for dbt (data build tool) providing integration with dbt Core/Cloud CLI, project metadata discovery, model information, and semantic layer querying capabilities.

Capabilities

  • get_all_models

    Explore your dbt project’s data models — ask for all models with `get_all_models`, then inspect any node’s full details via `get_node_details`.

  • get_lineage

    Trace upstream and downstream lineage — use `get_lineage` to see ancestors and descendants for a model, filtered by type and depth.

  • list_metrics

    Query metrics through the Semantic Layer — list available metrics with `list_metrics`, then run filtered, grouped metric queries via `query_metrics`.

  • get_model_health

    Check model health and performance — retrieve run status, test results, and source freshness with `get_model_health`, or get execution history via `get_model_performance`.

  • generate_model_yaml

    Generate project boilerplate — create model YAML, source YAML, or staging model SQL using `generate_model_yaml`, `generate_source`, and `generate_staging_model`.

  • list_jobs

    Manage dbt Cloud jobs — list and trigger jobs with `list_jobs` and `trigger_job_run`, then inspect run details or artifacts using `get_job_run_details` and `list_job_run_artifacts`.

Tags

  • database
  • analytics
  • data-analysis
  • sql
  • devops-infrastructure
  • awesome-list

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