Integrations
Provides access to dbt project metadata through manifest.json and catalog.json artifacts, enabling search of models, sources, and tests, inspection of node attributes, exploration of model dependencies, and tracing of column-level lineage within dbt projects.
Used for progress visualization when processing potentially large dbt manifests, particularly during column-level lineage creation which can take hours for larger projects.
dbt-docs-mcp
Model Context Protocol (MCP) server for interacting with dbt project metadata, including dbt Docs artifacts (manifest.json
, catalog.json
). This server exposes dbt graph information and allows querying node details, model/column lineage, and related metadata.
Key Functionality
This server provides tools to:
- Search dbt Nodes:
- Find nodes (models, sources, tests, etc.) by name (
search_dbt_node_names
). - Locate nodes based on column names (
search_dbt_column_names
). - Search within the compiled SQL code of nodes (
search_dbt_sql_code
).
- Find nodes (models, sources, tests, etc.) by name (
- Inspect Nodes:
- Retrieve detailed attributes for any given node unique ID (
get_dbt_node_attributes
).
- Retrieve detailed attributes for any given node unique ID (
- Explore Lineage:
- Find direct upstream dependencies (predecessors) of a node (
get_dbt_predecessors
). - Find direct downstream dependents (successors) of a node (
get_dbt_successors
).
- Find direct upstream dependencies (predecessors) of a node (
- Column-Level Lineage:
- Trace all upstream sources for a specific column in a model (
get_column_ancestors
). - Trace all downstream dependents of a specific column in a model (
get_column_descendants
).
- Trace all upstream sources for a specific column in a model (
- Suggested extensions:
- Tool that allows executing SQL queries.
- Tool that retrieves table/view/column metadata directly from the database.
- Tool to search knowledge-base.
Getting Started
- Prerequisites: Ensure you have Python installed and uv
- Clone the repo:Copy
- Optional: parse dbt manifest for column-level lineage:
- Setup the required Python environment, e.g.:
Copy- Use the provided script
scripts/create_manifest_cl.py
and simply provide the path to your dbt manifest, dbt catalog and the desired output paths for your schema and column lineage file:
Copy- Depending on your dbt project size, creating column-lineage can take a while (hours)
- Run the Server:
- If your desired MCP client (Claude desktop, Cursor, etc.) supports mcp.json it would like as below:
Copy
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
dbt-docs-mcp
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