dbt MCP Server

@kannandreams

Basic information

About dbt MCP Server

dbt-mcp-server

dbt MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "dbt-mcp-server": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "dbt-mcp-server",
        "."
      ]
    }
  }
}

dbt MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is dbt MCP Server?

The dbt MCP Server is a minimal, extensible MCP (Model Context Protocol) server that provides a unified JSON-based interface for running dbt models, tests, and other dbt operations. It can be triggered via CLI, HTTP API, or an AI interface like Claude, and includes Slack notifications for task completions.

How to use dbt MCP Server?

Run the server locally with uvicorn mcp_dispatcher:app --reload --port 8000 or use Docker with docker build -t dbt-mcp-server . then docker run -p 8000:8000 dbt-mcp-server. Trigger dbt models by executing python mcp_dispatcher.py mcp_request.json with a JSON spec. Integrate with Claude via python claude_client_example.py. Set the SLACK_WEBHOOK_URL environment variable to receive Slack alerts.

Key features of dbt MCP Server

Run dbt models using a clean JSON spec
Accept CLI or HTTP API calls
Slack alerts for model success or failure
Compatible with AI tools like Claude
Extensible and minimal design
Unified interface for triggering dbt operations

Use cases of dbt MCP Server

Automate dbt model runs by chatting with Claude
Trigger dbt tests and models via a REST API
Receive immediate Slack notifications on model completion or errors
Integrate dbt into AI-driven data pipelines

Frequently asked questions

What does this server do compared to other dbt tools?

It provides a minimal, extensible MCP interface to trigger dbt models and tests using a unified JSON spec, making it easy to integrate with AI assistants like Claude.

What are the runtime requirements?

You need Python with uvicorn to run locally, or Docker for containerized deployment. The server runs on port 8000.

How do I get Slack alerts?

Set the `SLACK_WEBHOOK_URL` environment variable to your Slack webhook URL. Alerts are sent on model success or failure.

How can I use this with Claude?

Run the provided `claude_client_example.py` script after starting the server. This allows Claude to trigger dbt operations via the MCP interface.

What license does this server use?

It is licensed under the MIT License, allowing free use, modification, and distribution.

Comments

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