dbt

MCP server by dbt Labs

Give assistants dbt project context: models, lineage, Semantic Layer metrics, Discovery API data and dbt CLI commands.

Runs locally (Runs on your machine: its page has the install command)Runs with uvx

Install dbt

Runs on your machine. Your client starts it with this command:

uvx dbt-mcp

Needs uv (Python) on your computer. The setup steps below show where the command goes in each client.

  • DBT_PROJECT_DIR Path to your dbt project.
  • DBT_PATH Path to the dbt executable.
Add to Cursor (opens in a new tab)Add to VS Code (opens in a new tab)

Share this server

Opens this page, with the install command and setup steps.

mcp.tc/i/dbt

About

Connects an AI assistant to dbt Core, dbt Fusion and the dbt platform. It can list models, sources and exposures, trace lineage, query Semantic Layer metrics, run dbt CLI commands, generate YAML and staging models, manage platform jobs and runs, and fetch pages from the dbt docs.

It runs locally over stdio with uvx dbt-mcp. The CLI tools need DBT_PROJECT_DIR and DBT_PATH. Semantic Layer, Discovery, Admin API and SQL tools need a dbt platform host (DBT_HOST) and a token (DBT_TOKEN). CLI commands such as run and build can modify warehouse objects, so use them only with a client you trust.

What you can do

  • Query Semantic Layer metrics, dimensions and entities
  • Browse models, sources, macros and exposures via the Discovery API
  • Trace model and column-level lineage
  • Run dbt build, run, test, compile and show from the CLI
  • Generate source YAML, model YAML and staging models
  • List, trigger, retry and cancel dbt platform jobs and runs
  • Search and fetch official dbt documentation pages

Tools

Local servers list their tools once they’re running, and this one doesn’t publish its list in advance. Your client shows them after you add it.

Example prompts

  • List all metrics defined in our dbt Semantic Layer

  • Show the upstream and downstream lineage of the orders model

  • Run dbt test for the staging models and summarize failures

  • Generate staging model SQL for the raw customers source table

Set up

Every client starts dbt on your machine with the same command. Pick yours; the page remembers your choice.

Claude Code

  1. Run this in a terminal, in your project folder:
claude mcp add --transport stdio dbt --env "DBT_PROJECT_DIR=<YOUR_DBT_PROJECT_DIR>" --env "DBT_PATH=<YOUR_DBT_PATH>" -- uvx dbt-mcp
  1. Start Claude Code and type /mcp. dbt should show as connected.

Add --scope user to make it available in every project. Replace the placeholders with your own values.

Claude Desktop

  1. Open Settings → Developer → Edit Config. It opens claude_desktop_config.json. Add:
claude_desktop_config.json
{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ],
      "env": {
        "DBT_PROJECT_DIR": "<YOUR_DBT_PROJECT_DIR>",
        "DBT_PATH": "<YOUR_DBT_PATH>"
      }
    }
  }
}
  1. Save the file and restart Claude Desktop. Replace the placeholders with your own values.

Needs uv (Python) on your computer. The file lives in ~/Library/Application Support/Claude/ on macOS and %APPDATA%\Claude\ on Windows.

Cursor

Add to Cursor (opens in a new tab)

Or add it by hand to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (this project):

mcp.json
{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ],
      "env": {
        "DBT_PROJECT_DIR": "<YOUR_DBT_PROJECT_DIR>",
        "DBT_PATH": "<YOUR_DBT_PATH>"
      }
    }
  }
}

Needs uv (Python) on your computer. Replace the placeholders with your own values.

VS Code

Install in VS Code (opens in a new tab)

Or from a terminal:

code --add-mcp '{"name":"dbt","type":"stdio","command":"uvx","args":["dbt-mcp"],"env":{"DBT_PROJECT_DIR":"<YOUR_DBT_PROJECT_DIR>","DBT_PATH":"<YOUR_DBT_PATH>"}}'

Or commit it to the repo in .vscode/mcp.json:

.vscode/mcp.json
{
  "servers": {
    "dbt": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ],
      "env": {
        "DBT_PROJECT_DIR": "<YOUR_DBT_PROJECT_DIR>",
        "DBT_PATH": "<YOUR_DBT_PATH>"
      }
    }
  }
}

Needs uv (Python) on your computer.

Devin Desktop

  1. Add it to ~/.config/devin/mcp_config.json (macOS and Linux) or %APPDATA%\devin\mcp_config.json (Windows):
mcp_config.json
{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ],
      "env": {
        "DBT_PROJECT_DIR": "<YOUR_DBT_PROJECT_DIR>",
        "DBT_PATH": "<YOUR_DBT_PATH>"
      }
    }
  }
}
  1. Refresh the MCP server list in Cascade. Replace the placeholders with your own values.

Devin Desktop is the new name for Windsurf.

Codex

codex mcp add dbt --env "DBT_PROJECT_DIR=<YOUR_DBT_PROJECT_DIR>" --env "DBT_PATH=<YOUR_DBT_PATH>" -- uvx dbt-mcp

Or edit ~/.codex/config.toml directly:

config.toml
[mcp_servers.dbt]
command = "uvx"
args = ["dbt-mcp"]
env = { DBT_PROJECT_DIR = "<YOUR_DBT_PROJECT_DIR>", DBT_PATH = "<YOUR_DBT_PATH>" }

Needs uv (Python) on your computer. Replace the placeholders with your own values.

Gemini CLI

gemini mcp add -e "DBT_PROJECT_DIR=<YOUR_DBT_PROJECT_DIR>" -e "DBT_PATH=<YOUR_DBT_PATH>" dbt uvx dbt-mcp

This adds it to the current project. Add -s user to use it everywhere.

Any client

Most clients that start local servers accept this shape:

{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": [
        "dbt-mcp"
      ],
      "env": {
        "DBT_PROJECT_DIR": "<YOUR_DBT_PROJECT_DIR>",
        "DBT_PATH": "<YOUR_DBT_PATH>"
      }
    }
  }
}

Zed puts servers under context_servers in its settings, with the same command, args and env fields.

Needs uv (Python) on your computer. Replace the placeholders with your own values.

FAQ

Can I paste mcp.tc/i/dbt into my MCP client?

No. dbt runs on your own computer, started by your client, so it has no web address to connect to. The quick link is the page to share; the install command is uvx dbt-mcp.

Does dbt need an API key?

No. It reads DBT_PROJECT_DIR and DBT_PATH from its environment; the setup steps show where to set them.

Is dbt a remote or a local server?

Local. Your client starts it as a process on your computer with uvx dbt-mcp, which needs uv (Python).

What can dbt do?

You can query Semantic Layer metrics, dimensions and entities, browse models, sources, macros and exposures via the Discovery API and trace model and column-level lineage.

Which clients can use it?

Any client that starts local servers: Claude Code, Claude Desktop, Cursor, VS Code, Devin Desktop, Codex, Gemini CLI, Zed and others. claude.ai and ChatGPT only connect to remote servers.

Who wrote this page?

mcp.tc’s robot read dbt’s public metadata (its package and repository pages), and an AI model drafted the text from it. A person reviews anything the checks can’t confirm. The text can still be wrong, so if you spot a mistake, use Report this listing on this page.

Embed

Show dbt in a README or on your site. Each embed links to this page, uses the server’s own install command, and sets no cookies. How embeds work

README badge

Badge preview, lightBadge preview, dark
Markdown
[![dbt on mcp.tc](https://mcp.tc/i/dbt/badge.svg)](https://mcp.tc/i/dbt)
HTML
<a href="https://mcp.tc/i/dbt"><img src="https://mcp.tc/i/dbt/badge.svg" alt="dbt on mcp.tc" height="20"></a>

It follows the reader’s light or dark mode. Add ?theme=light or ?theme=dark to fix it, or ?style=compact to show the mark without the word.

Website card

HTML
<script src="https://mcp.tc/w/dbt.js" async></script>

The card appears where the tag is. Add data-theme="dark" or data-size="compact" to the tag to change it. The file holds everything it needs, so it makes no other requests and sets no cookies.

iframe

HTML
<iframe src="https://mcp.tc/embed/dbt" title="dbt on mcp.tc" width="420" height="200" loading="lazy" allow="clipboard-write" style="border:0;border-radius:8px;max-width:100%"></iframe>

Use it on pages that don’t allow scripts. Add ?theme=light or ?theme=dark to the address to fix the colors.

JSON

The listing as data for your own pages and tools: name, tagline, install command, tools and the “Add to” links. Any site can read it (CORS is open).

https://mcp.tc/i/dbt.json

What each field means

Related servers

More in Databases & Backend

  • Upstash

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Manage Upstash Redis, QStash, Workflow and Box resources and debug them from your agent through the Upstash Developer API.

    mcp.tc/i/upstash

  • Convex

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Inspect tables, query data and run functions in Convex deployments from your AI assistant.

    mcp.tc/i/convex

  • Neo4j, verified

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Read the schema and run read or write Cypher queries on a Neo4j graph database.

    mcp.tc/i/neo4j

  • Pinecone, verified

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Search Pinecone docs and create, upsert into and query Pinecone indexes with integrated inference from your coding assistant.

    mcp.tc/i/pinecone

  • Qdrant

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Store and retrieve semantic memories in a Qdrant vector database collection.

    mcp.tc/i/qdrant

  • Redis, verified

    Databases & Backend

    Local (Runs on your machine: its page has the install command)

    Read and write Redis data structures, vector search indexes and streams in natural language.

    mcp.tc/i/redis

mcp.tc isn’t affiliated with dbt Labs. This page was built from dbt’s public metadata, last checked on 3 Oct 2026, and an AI model wrote the description, so it can be wrong. Names and marks belong to their owners. Something off? Report this listing.