version: "1.0.1" name: configuring-dbt-mcp-server description: Generates MCP server configuration JSON, resolves authentication setup, and validates server connectivity for dbt. Use when setting up, configuring, or troubleshooting the dbt MCP server for AI tools like Claude Desktop, Claude Code, Cursor, or VS Code. user-invocable: false metadata: author: dbt-labs

Configure dbt MCP Server

Overview

The dbt MCP server connects AI tools to dbt's CLI, Semantic Layer, Discovery API, and Admin API. This skill guides users through setup with the correct configuration for their use case.

Decision Flow

flowchart TB
    start([User wants dbt MCP]) --> q1{Local or Remote?}
    q1 -->|dev workflows,<br>CLI access needed| local[Local Server<br>uvx dbt-mcp]
    q1 -->|consumption only,<br>no local install| remote[Remote Server<br>HTTP endpoint]
    local --> q2{Which client?}
    remote --> q2
    q2 --> claude_desktop[Claude Desktop]
    q2 --> claude_code[Claude Code]
    q2 --> cursor[Cursor]
    q2 --> vscode[VS Code]
    claude_desktop --> config[Generate config<br>+ test setup]
    claude_code --> config
    cursor --> config
    vscode --> config

Questions to Ask

1. Server Type

Ask: "Do you want to use the local or remote dbt MCP server?"

2. MCP Client

Ask: "Which MCP client are you using?"

• Claude Desktop
• Claude Code (CLI)
• Cursor
• VS Code

3. Use Case (Local Server Only)

Ask: "What's your use case?"

4. Tools to Enable

Ask: "Which tools do you want enabled?" (show defaults)

Prerequisites

Local Server

1. Install `uv`: https://docs.astral.sh/uv/getting-started/installation/
2. Have a dbt project (for CLI commands)
3. Find paths:

• DBT_PROJECT_DIR: Folder containing dbt_project.yml
• macOS/Linux: pwd from project folder
• Windows: Full path with forward slashes (e.g., C:/Users/name/project)
• DBT_PATH: Path to dbt executable
• macOS/Linux: which dbt
• Windows: where dbt

Remote Server

1. dbt Cloud account with AI features enabled
2. Production environment ID (from Orchestration page)
3. Personal access token or service token

See How to Find Your Credentials for detailed guidance on obtaining tokens and IDs.

Credential Security

• Always use environment variable references (e.g., ${DBT_TOKEN}) instead of literal token values in configuration files that may be committed to version control
• Never log, display, or echo token values in terminal output
• When using .env files, ensure they are added to .gitignore to prevent accidental commits
• Recommend users rotate tokens regularly and use the minimum required permission set

Configuration Templates

Local Server - CLI Only

{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": ["dbt-mcp"],
      "env": {
        "DBT_PROJECT_DIR": "/path/to/your/dbt/project",
        "DBT_PATH": "/path/to/dbt"
      }
    }
  }
}

Local Server - Platform + CLI (OAuth)

{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": ["dbt-mcp"],
      "env": {
        "DBT_HOST": "https://your-subdomain.us1.dbt.com",
        "DBT_PROJECT_DIR": "/path/to/project",
        "DBT_PATH": "/path/to/dbt"
      }
    }
  }
}

Local Server - Platform + CLI (Token Auth)

{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": ["dbt-mcp"],
      "env": {
        "DBT_HOST": "cloud.getdbt.com",
        "DBT_TOKEN": "${DBT_TOKEN}",
        "DBT_ACCOUNT_ID": "${DBT_ACCOUNT_ID}",
        "DBT_PROD_ENV_ID": "${DBT_PROD_ENV_ID}",
        "DBT_PROJECT_DIR": "/path/to/project",
        "DBT_PATH": "/path/to/dbt"
      }
    }
  }
}

Local Server - Using .env File

{
  "mcpServers": {
    "dbt": {
      "command": "uvx",
      "args": ["--env-file", "/path/to/.env", "dbt-mcp"]
    }
  }
}

.env file contents:

DBT_HOST=cloud.getdbt.com
DBT_TOKEN=<set-via-env-or-secret-manager>
DBT_ACCOUNT_ID=<your-account-id>
DBT_PROD_ENV_ID=<your-prod-env-id>
DBT_DEV_ENV_ID=<your-dev-env-id>
DBT_USER_ID=<your-user-id>
DBT_PROJECT_DIR=/path/to/project
DBT_PATH=/path/to/dbt

Remote Server

{
  "mcpServers": {
    "dbt": {
      "url": "https://cloud.getdbt.com/api/ai/v1/mcp/",
      "headers": {
        "Authorization": "Token ${DBT_TOKEN}",
        "x-dbt-prod-environment-id": "${DBT_PROD_ENV_ID}"
      }
    }
  }
}

Additional headers for SQL/Fusion tools:

{
  "headers": {
    "Authorization": "Token ${DBT_TOKEN}",
    "x-dbt-prod-environment-id": "${DBT_PROD_ENV_ID}",
    "x-dbt-dev-environment-id": "${DBT_DEV_ENV_ID}",
    "x-dbt-user-id": "${DBT_USER_ID}"
  }
}

Client-Specific Setup

Claude Desktop

1. Click Claude menu in system menu bar (not in-app)
2. Select Settings...
3. Go to Developer tab
4. Click Edit Config
5. Add the JSON configuration
6. Save and restart Claude Desktop
7. Verify: Look for MCP server indicator in bottom-right of input box

Config location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Claude Code (CLI)

Run:

claude mcp add dbt -s user -- uvx dbt-mcp

This adds the server to your user scope/config (on this system: ~/.claude.json).

For a project-specific setup, run:

claude mcp add dbt -s project -- uvx dbt-mcp

This adds the server to .mcp.json in your project root.

Alternatively, you can use the manual configuration below.

Manual configuration: Edit ~/.claude.json (user scope) or create .mcp.json (project scope) in your project root:

• ~/.claude.json: Global across all projects
• .mcp.json: Project-specific, can be committed to version control for team sharing. If using token auth, use environment variable references — never commit literal tokens.

For project-specific dbt setups, use .mcp.json so your team shares the same configuration.

Once the config is created, make sure to add the JSON configuration under the mcpServers key.

Cursor

1. Open Cursor menu → Settings → Cursor Settings → MCP
2. Add the JSON configuration
3. Update paths and credentials
4. Save

VS Code

1. Open Command Palette (Cmd/Ctrl + Shift + P)
2. Run "MCP: Open User Configuration" (or Workspace for project-specific)
3. Add the JSON configuration (note: VS Code uses servers not mcpServers):

{
  "servers": {
    "dbt": {
      "command": "uvx",
      "args": ["dbt-mcp"],
      "env": {
        "DBT_PROJECT_DIR": "/path/to/project",
        "DBT_PATH": "/path/to/dbt"
      }
    }
  }
}

1. Open Settings → Features → Chat → Enable MCP
2. Verify: Run "MCP: List Servers" from Command Palette

WSL Users: Configure in Remote settings, not local user settings:

• Run "Preferences: Open Remote Settings" from Command Palette
• Use full Linux paths (e.g., /home/user/project, not Windows paths)

Verification Steps

Test Local Server Config

Recommended: Use .env file

1. Create a .env file in your project root directory and add minimum environment variables for the CLI tools:

DBT_PROJECT_DIR=/path/to/project
DBT_PATH=/path/to/dbt

1. Test the server:

uvx --env-file .env dbt-mcp

Alternative: Environment variables

# Temporary test (variables only last for this session)
export DBT_PROJECT_DIR=/path/to/project
export DBT_PATH=/path/to/dbt
uvx dbt-mcp

No errors = successful configuration.

Verify in Client

After setup, ask the AI:

• "What dbt tools do you have access to?"
• "List my dbt metrics" (if Semantic Layer enabled)
• "Show my dbt models" (if Discovery enabled)

See Troubleshooting for common issues and fixes.

See Environment Variable Reference for the full list of supported variables.