dbt-docs
About
MCP server for dbt-core (OSS) users as the official dbt MCP only supports dbt Cloud. Supports project metadata, model and column-level lineage and dbt documentation.
Details
- License
- MIT
Explore
- Search nodes by name, column name, or compiled SQL.
- Retrieve detailed attributes of any node by unique ID.
- Find direct upstream predecessors of a node.
- Find direct downstream successors of a node.
- Trace column-level ancestors and descendants.
- Supports extensions for SQL execution and database metadata.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
dbt-docsCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
1. Prerequisites: Ensure you have Python installed and uv
2. Clone the repo:
git clone <repository-url>
cd dbt-docs-mcp
3. Optional: parse dbt manifest for column-level lineage:
- Setup the required Python environment, e.g.:
uv sync
- 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: python scripts/create_manifest_cl.py --manifest-path PATH_TO_YOUR_MANIFEST_FILE --catalog-path PATH_TO_YOUR_CATALOG_FILE --schema-mapping-path DESIRED_OUTPUT_PATH_FOR_SCHEMA_MAPPING --manifest-cl-path DESIRED_OUTPUT_PATH_FOR_MANIFEST_CL
- Depending on your dbt project size, creating column-lineage can take a while (hours)
4. Run the Server:
- If your desired MCP client (Claude desktop, Cursor, etc.) supports mcp.json it would look as below:
{
"mcpServers": {
"DBT Docs MCP": {
"command": "uv",
"args": [
"run",
"--with",
"networkx,mcp[cli],rapidfuzz,dbt-core,python-decouple,sqlglot,tqdm",
"mcp",
"run",
"/Users/mattijs/repos/dbt-docs-mcp/src/mcp_server.py"
],
"env": {
"MANIFEST_PATH": "/Users/mattijs/repos/dbt-docs-mcp/inputs/manifest.json",
"SCHEMA_MAPPING_PATH": "/Users/mattijs/repos/dbt-docs-mcp/outputs/schema_mapping.json",
"MANIFEST_CL_PATH": "/Users/mattijs/repos/dbt-docs-mcp/outputs/manifest_column_lineage.json"
}
}
}
}
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"dbt-docs": {
"dbt-docs-mcp": {
"command": "uv",
"args": [
"sync"
]
}
}
}
}McpServers
{
"dbt-docs-mcp": {
"command": "uv",
"args": [
"sync"
]
}
}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).
Inspect Nodes:
Retrieve detailed attributes for any given node unique ID (get_dbt_node_attributes).
Explore Lineage:
Find direct upstream dependencies (predecessors) of a node (get_dbt_predecessors).
Find direct downstream dependents (successors) of a node (get_dbt_successors).
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).
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
1. Prerequisites: Ensure you have Python installed and uv
2. Clone the repo:
git clone <repository-url>
cd dbt-docs-mcp
3. Optional: parse dbt manifest for column-level lineage:
- Setup the required Python environment, e.g.:
uv sync
- 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: python scripts/create_manifest_cl.py --manifest-path PATH_TO_YOUR_MANIFEST_FILE --catalog-path PATH_TO_YOUR_CATALOG_FILE --schema-mapping-path DESIRED_OUTPUT_PATH_FOR_SCHEMA_MAPPING --manifest-cl-path DESIRED_OUTPUT_PATH_FOR_MANIFEST_CL
- Depending on your dbt project size, creating column-lineage can take a while (hours)
4. Run the Server:
- If your desired MCP client (Claude desktop, Cursor, etc.) supports mcp.json it would look as below:
{
"mcpServers": {
"DBT Docs MCP": {
"command": "uv",
"args": [
"run",
"--with",
"networkx,mcp[cli],rapidfuzz,dbt-core,python-decouple,sqlglot,tqdm",
"mcp",
"run",
"/Users/mattijs/repos/dbt-docs-mcp/src/mcp_server.py"
],
"env": {
"MANIFEST_PATH": "/Users/mattijs/repos/dbt-docs-mcp/inputs/manifest.json",
"SCHEMA_MAPPING_PATH": "/Users/mattijs/repos/dbt-docs-mcp/outputs/schema_mapping.json",
"MANIFEST_CL_PATH": "/Users/mattijs/repos/dbt-docs-mcp/outputs/manifest_column_lineage.json"
}
}
}
}
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