dbt

dbt MCP Server

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.

Tools

SQL

• 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

• 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

• 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

• build: Executes models, tests, snapshots, and seeds in DAG order.
• 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

• cancel_job_run: Cancels a running job.
• get_job_details: Gets job configuration including triggers, schedule, and dbt commands.
• get_job_run_artifact: Downloads a specific artifact file from a job run.
• 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.
• get_project_details: Gets project information for a specific dbt project.
• 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.
• 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

• 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

• 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).

MCP Server Metadata

• 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!