# dbt MCP Server This MCP (Model Context Protocol) server provides tools to interact with dbt. Read [this](https://docs.getdbt.com/blog/introducing-dbt-mcp-server) blog to learn more. ## Architecture  ## Setup 1. Clone the repository: \`\`\`shell git clone https://github.com/dbt-labs/dbt-mcp.git cd dbt-mcp \`\`\` 2. [Install uv](https://docs.astral.sh/uv/getting-started/installation/) 3. [Install Task](https://taskfile.dev/installation/) 4. Run \`task install\` 5. Configure environment variables: \`\`\`shell cp .env.example .env \`\`\` Then edit \`.env\` with your specific environment variables (see the \`Configuration\` section of the \`README.md\`). ## Configuration The MCP server takes the following configuration: ### Tool Groups | Name | Default | Description | |------|---------|-------------| | \`DISABLE_DBT_CLI\` | \`false\` | Set this to \`true\` to disable dbt Core and dbt Cloud CLI MCP tools | | \`DISABLE_SEMANTIC_LAYER\` | \`false\` | Set this to \`true\` to disable dbt Semantic Layer MCP objects | | \`DISABLE_DISCOVERY\` | \`false\` | Set this to \`true\` to disable dbt Discovery API MCP objects | | \`DISABLE_REMOTE\` | \`true\` | Set this to \`false\` to enable remote MCP objects | ### Configuration for Discovery and Semantic Layer | Name | Default | Description | |------|---------|-------------| | \`DBT_HOST\` | \`cloud.getdbt.com\` | Your dbt Cloud instance hostname. This will look like an \`Access URL\` found [here](https://docs.getdbt.com/docs/cloud/about-cloud/access-regions-ip-addresses). If you are using Multi-cell, do not include the \`ACCOUNT_PREFIX\` here | | \`MULTICELL_ACCOUNT_PREFIX\` | - | If you are using Multi-cell, set this to your \`ACCOUNT_PREFIX\`. If you are not using Multi-cell, do not set this environment variable. You can learn more [here](https://docs.getdbt.com/docs/cloud/about-cloud/access-regions-ip-addresses) | | \`DBT_TOKEN\` | - | Your personal access token or service token. **Note** Service token is required when using the Semantic Layer | | \`DBT_PROD_ENV_ID\` | - | Your dbt Cloud production environment ID | ### Configuration for Remote Tools | Name | Description | |------|-------------| | \`DBT_DEV_ENV_ID\` | Your dbt Cloud development environment ID | | \`DBT_USER_ID\` | Your dbt Cloud user ID | ### Configuration for dbt CLI | Name | Description | |------|-------------| | \`DBT_PROJECT_DIR\` | The path to where the repository of your dbt Project is hosted locally. This should look something like \`/Users/firstnamelastname/reponame\` | | \`DBT_PATH\` | The path to your dbt Core or dbt Cloud CLI executable. You can find your dbt executable by running \`which dbt\` | ## Using with MCP Clients After going through [Installation](#installation), you can use your server with an MCP client. This configuration will be added to the respective client's config file. Be sure to replace the sections within \`<>\`: \`\`\`json \{ "mcpServers": \{ "dbt-mcp": \{ "command": "", "args": [ "run", "/src/dbt_mcp/main.py" ] \} \} \} \`\`\` \`\` depends on your OS: - Linux & Mac: \`/.venv/bin/mcp\` - PC: \`/.venv/Scripts/mcp\` ## Claude Desktop Follow [these](https://modelcontextprotocol.io/quickstart/user) instructions to create the \`claude_desktop_config.json\` file and connect. On Mac, you can find the Claude Desktop logs at \`~/Library/Logs/Claude\`. ## Cursor 1. Open the Cursor menu and select Settings → Cursor Settings → MCP 2. Click "Add new global MCP server" 3. Add the config from above to the provided \`mcp.json\` file 4. Verify your connection is active within the MCP tab Cursor MCP docs [here](https://docs.cursor.com/context/model-context-protocol) for reference ## VS Code 1. Open the Settings menu (Command + Comma) and select the correct tab atop the page for your use case - \`Workspace\` - configures the server in the context of your workspace - \`User\` - configures the server in the context of your user - **Note for WSL users**: If you're using VS Code with WSL, you'll need to configure WSL-specific settings. Run the **Preferences: Open Remote Settings** command from the Command Palette (F1) or select the **Remote** tab in the Settings editor. Local User settings are reused in WSL but can be overridden with WSL-specific settings. Configuring MCP servers in the local User settings will not work properly in a WSL environment. 2. Select Features → Chat 3. Ensure that "Mcp" is \`Enabled\`  4. Click "Edit in settings.json" under "Mcp > Discovery" 5. Add your server configuration (\`dbt\`) to the provided \`settings.json\` file as one of the servers: \`\`\`json \{ "mcp": \{ "inputs": [], "servers": \{ "dbt": \{ "command": "", "args": ["run", "/src/dbt_mcp/main.py"] \} \} \} \} \`\`\` \`\` depends on your OS: - Linux & Mac: \`/.venv/bin/mcp\` - PC: \`/.venv/Scripts/mcp\` 6. You can start, stop, and configure your MCP servers by: - Running the \`MCP: List Servers\` command from the Command Palette (Control + Command + P) and selecting the server - Utlizing the keywords inline within the \`settings.json\` file  VS Code MCP docs [here](https://code.visualstudio.com/docs/copilot/chat/mcp-servers) for reference ## Tools ### dbt CLI * \`build\` - Executes models, tests, snapshots, and seeds in dependency order * \`compile\` - Generates executable SQL from models, tests, and analyses without running them * \`docs\` - Generates documentation for the dbt project * \`ls\` (list) - Lists resources in the dbt project, such as models and tests * \`parse\` - Parses and validates the project’s files for syntax correctness * \`run\` - Executes models to materialize them in the database * \`test\` - Runs tests to validate data and model integrity * \`show\` - Runs a query against the data warehouse > Allowing your client to utilize dbt commands through this MCP tooling could modify your data models, sources, and warehouse objects. Proceed only if you trust the client and understand the potential impact. ### Semantic Layer * \`list_metrics\` - Retrieves all defined metrics * \`get_dimensions\` - Gets dimensions associated with specified metrics * \`get_entities\` - Gets entities associated with specified metrics * \`query_metrics\` - Queries metrics with optional grouping, ordering, filtering, and limiting ### Discovery * \`get_mart_models\` - Gets all mart models * \`get_all_models\` - Gets all models * \`get_model_details\` - Gets details for a specific model * \`get_model_parents\` - Gets parent nodes of a specific model * \`get_model_children\` - Gets children modes of a specific model ## Contributing Read \`CONTRIBUTING.md\` for instructions on how to get involved!