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MCP server · Data

dbt-labs/dbt-mcp

A MCP (Model Context Protocol) server for interacting with dbt.

92Excellent

Scored yesterday · breakdown

About dbt-labs/dbt-mcp

dbt-labs/dbt-mcp is an MCP server published by dbt-labs in the Data category: a MCP (Model Context Protocol) server for interacting with dbt. It has been installed 0 times through Conduid.

The repository has 502 stars and 106 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx dbt-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

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  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v2.2.0v2.2.0 · 25 Aug 2026v2.2.0 - 2026-08-25 Enhancement or New Feature Add an optional `dbt_version_override` parameter to `trigger_job_run`, so a run can be executed on a different dbt version without changing the job or its environment.
v2.1.2v2.1.2 · 20 Aug 2026v2.1.2 - 2026-08-20 Under the Hood Fix release pull request checks and sign automated release commits. Bug Fix Cleanup of the local OAuth helper: file permissions and response payload.
v2.1.1v2.1.1 · 19 Aug 2026v2.1.1 - 2026-08-19 Under the Hood Update the PyPI publishing action to support Core Metadata 2.5.
v2.1.0v2.1.0 · 18 Aug 2026v2.1.0 - 2026-08-17 Enhancement or New Feature Return the exact adapter-rendered relation name for models from node detail queries.
v2.0.0-beta.1v2.0.0-beta.1 · 30 Jul 2026v2.0.0-beta.1 - 2026-07-30 Breaking Change get_lineage (single- and multi-project) now returns a structured lineage graph (root_id/nodes/edges) instead of a list of node dicts, and links an interactive MCP-app UI that supporting MCP hosts…

README

dbt MCP Server

OpenSSF Best Practices

This MCP (Model Context Protocol) server provides various tools to interact with dbt. You can use this MCP server to provide AI agents with context of your project in dbt Core, dbt Fusion, and dbt Platform.

Read our documentation here to learn more. This blog post provides more details for what is possible with the dbt MCP server.

Experimental MCP Bundle

We publish an experimental Model Context Protocol Bundle (dbt-mcp.mcpb) with each release so that MCPB-aware clients can import this server without additional setup. Download the bundle from the latest release assets and follow Anthropic's mcpb CLI docs to install or inspect it.

Feedback

If you have comments or questions, create a GitHub Issue or join us in the community Slack in the #tools-dbt-mcp channel.

Architecture

The dbt MCP server architecture allows for your agent to connect to a variety of tools.

architecture diagram of the dbt MCP server

Tools

SQL

Tools for executing and generating SQL on dbt Platform infrastructure.

  • execute_sql: Executes SQL on dbt Platform infrastructure with Semantic Layer support.
  • text_to_sql: Generates SQL from natural language using project context.

Semantic Layer

To learn more about the dbt Semantic Layer, click here.

  • get_dimensions: Gets dimensions for specified metrics.
  • get_entities: Gets entities for specified metrics.
  • get_metrics_compiled_sql: Returns compiled SQL for metrics without executing the query.
  • list_metrics: Retrieves all defined metrics.
  • list_saved_queries: Retrieves all saved queries.
  • query_metrics: Executes metric queries with filtering and grouping options.

Discovery

To learn more about the dbt Discovery API, click here.

  • get_all_macros: Retrieves macros; option to filter by package or return package names only.
  • get_all_models: Retrieves name and description of all models.
  • get_all_sources: Gets all sources with freshness status; option to filter by source name.
  • get_exposure_details: Gets exposure details including owner, parents, and freshness status.
  • get_exposures: Gets all exposures (downstream dashboards, apps, or analyses).
  • get_lineage: Gets full lineage graph (ancestors and descendants) with type and depth filtering.
  • get_macro_details: Gets details for a specific macro.
  • get_mart_models: Retrieves all mart models.
  • get_model_children: Gets downstream dependents of a model.
  • get_model_details: Gets model details including compiled SQL, columns, and schema.
  • get_model_health: Gets health signals: run status, test results, and upstream source freshness.
  • get_model_parents: Gets upstream dependencies of a model.
  • get_model_performance: Gets execution history for a model; option to include test results.
  • get_related_models: Finds similar models using semantic search.
  • get_seed_details: Gets details for a specific seed.
  • get_semantic_model_details: Gets details for a specific semantic model.
  • get_snapshot_details: Gets details for a specific snapshot.
  • get_source_details: Gets source details including columns and freshness.
  • get_test_details: Gets details for a specific test.
  • search: [Alpha] Searches for resources across the dbt project (not generally available).

dbt CLI

Allowing your client to utilize dbt commands through the MCP tooling could modify your data models, sources, and warehouse objects. Proceed only if you trust the client and understand the potential impact.

  • build: Executes models, tests, snapshots, and seeds in DAG order.
  • clone: Clones selected nodes from the specified state to the target schema(s).
  • compile: Generates executable SQL from models/tests/analyses; useful for validating Jinja logic.
  • docs: Generates documentation for the dbt project.
  • get_lineage_dev: Retrieves lineage from local manifest.json with type and depth filtering.
  • get_node_details_dev: Retrieves node details from local manifest.json (models, seeds, snapshots, sources).
  • list: Lists resources in the dbt project by type with selector support.
  • parse: Parses and validates project files for syntax correctness.
  • run: Executes models to materialize them in the database.
  • show: Executes SQL against the database and returns results.
  • test: Runs tests to validate data and model integrity.

Admin API

To learn more about the dbt Administrative API, click here.

  • cancel_job_run: Cancels a running job.
  • get_job_details: Gets job configuration including triggers, schedule, and dbt commands.
  • get_job_run_details: Gets run details including status, timing, steps, and artifacts.
  • get_job_run_error: Gets error and/or warning details for a job run; option to include or show warnings only.
  • list_job_run_artifacts: Lists available artifacts from a job run.
  • list_jobs: Lists jobs in a dbt Platform account; option to filter by project or environment.
  • list_jobs_runs: Lists job runs; option to filter by job, status, or order by field.
  • list_projects: Lists all projects in the dbt Platform account.
  • retry_job_run: Retries a failed job run.
  • trigger_job_run: Triggers a job run; option to override git branch, schema, or other settings.

dbt Codegen

These tools help automate boilerplate code generation for dbt project files.

  • generate_model_yaml: Generates model YAML with columns; option to inherit upstream descriptions.
  • generate_source: Generates source YAML by introspecting database schemas; option to include columns.
  • generate_staging_model: Generates staging model SQL from a source table.

dbt LSP

A set of tools that leverage the Fusion engine for advanced SQL compilation and column-level lineage analysis.

  • fusion.compile_sql: Compiles SQL in project context via dbt Platform.
  • fusion.get_column_lineage: Traces column-level lineage via dbt Platform.
  • get_column_lineage: Traces column-level lineage locally (requires dbt-lsp via dbt Labs VSCE).

Product Docs

Tools for searching and fetching content from the official dbt documentation at docs.getdbt.com.

  • get_product_doc_pages: Fetches the full Markdown content of one or more docs.getdbt.com pages by path or URL.
  • search_product_docs: Searches docs.getdbt.com for pages matching a query; returns titles, URLs, and descriptions ranked by relevance. Use get_product_doc_pages to fetch full content.

MCP Server Metadata

These tools provide information about the MCP server itself.

  • get_mcp_server_branch: Returns the current git branch of the running dbt MCP server.
  • get_mcp_server_version: Returns the current version of the dbt MCP server.

Examples

Commonly, you will connect the dbt MCP server to an agent product like Claude or Cursor. However, if you are interested in creating your own agent, check out the examples directory for how to get started.

Dependencies

Dependencies are pinned to specific versions and are not updated automatically. Only security-related dependency updates are submitted via automated pull requests.

Contributing

Read CONTRIBUTING.md for instructions on how to get involved!

README mirrored from the source repository yesterday. The original is authoritative.

Questions

About dbt-labs/dbt-mcp

How do I install dbt-labs/dbt-mcp?

Run npx dbt-mcp, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is dbt-labs/dbt-mcp safe to use with an AI agent?

Its trust score is 92 out of 100 (excellent). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is dbt-labs/dbt-mcp still maintained?

Yes — the latest release is v2.2.0 (25 Aug 2026), and the last commit was 6 months ago. The repository has 502 stars and 0 open issues.