dbt-mcp-server

dbt MCP Server Skill

Purpose

The dbt MCP server connects Claude Code (and Claude Desktop) to dbt's CLI, Semantic Layer, Discovery API, and Admin API. Once configured, other dbt skills (dbt-analytics-qa, dbt-semantic-layer, dbt-dag) can use MCP tools like list_metrics, get_lineage, get_mart_models, and dbt_build directly rather than falling back to manifest parsing.

This skill guides users through choosing the right server type, generating the correct configuration, and verifying the connection.

When This Skill Activates

User-Triggered Activation

• "How do I connect Claude to my dbt project?"
• "Set up the dbt MCP server"
• "I want Claude to be able to run dbt commands"
• "How do I use the dbt Semantic Layer with Claude?"
• "Configure dbt MCP for Claude Code"

Keywords: "dbt MCP", "dbt-mcp", "dbt MCP server", "dbt semantic layer MCP", "dbt Discovery API", "dbt tools", "uvx dbt-mcp"

Self-Triggered Activation

Activate when:

• Another dbt skill falls back to manifest parsing because MCP tools are unavailable
• The user asks why Claude can't see their dbt metrics or model lineage
• .mcp.json or ~/.claude.json are being edited in a Wire project

---

Step 1: Choose server type

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

	Local server	Remote server
How it runs	On your machine via uvx dbt-mcp	HTTP endpoint at dbt Cloud
dbt CLI access	Yes (dbt run, build, test, show)	No
Semantic Layer	Yes (if dbt Cloud connected)	Yes
Discovery API	Yes (if dbt Cloud connected)	Yes
Requires dbt Cloud	No (CLI-only mode works without it)	Yes
Credits consumed	No	Yes (dbt Copilot credits)
Best for	Wire project development work	Consumption/analytics Q&A only

Recommendation for Wire projects: Use local server. It gives Claude access to dbt CLI commands during development and connects to dbt Cloud for Semantic Layer / Discovery when needed.

---

Step 2: Choose what to enable

Defaults are sensible for Wire projects:

Category	Default	Disable with
dbt CLI (run, build, test, compile)	Enabled	DISABLE_DBT_CLI=true
Semantic Layer (metrics, dimensions)	Enabled	DISABLE_SEMANTIC_LAYER=true
Discovery API (models, lineage)	Enabled	DISABLE_DISCOVERY=true
Admin API (jobs, runs)	Enabled	DISABLE_ADMIN_API=true
SQL (text_to_sql, execute_sql)	Disabled	DISABLE_SQL=false to enable
Codegen (generate models/sources)	Disabled	DISABLE_DBT_CODEGEN=false to enable

---

Step 3: Prerequisites

Before generating the configuration, gather:

1. DBT_PROJECT_DIR: Absolute path to the folder containing dbt_project.yml

   # From inside your dbt project:
   pwd
   

2. DBT_PATH: Path to the dbt executable

   which dbt        # dbt Core in venv
   which dbtf       # dbt Fusion
   

3. dbt Cloud credentials (only needed for Semantic Layer, Discovery, Admin API):

   • DBT_HOST: your dbt Cloud host (e.g. https://your-account.us1.dbt.com or cloud.getdbt.com)
   • DBT_TOKEN: personal access token (Settings → API Access in dbt Cloud)
   • DBT_ACCOUNT_ID: from your dbt Cloud URL (cloud.getdbt.com/accounts/XXXXX)
   • DBT_PROD_ENV_ID: from Orchestration → Environments in dbt Cloud

---

Configuration Templates

Local server — CLI only (no dbt Cloud)

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

Local server — CLI + dbt Cloud (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 a .env file (recommended for teams)

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

.env file:

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_PROJECT_DIR=/path/to/project
DBT_PATH=/path/to/dbt

Add .env to .gitignore — never commit literal tokens.

Remote server (dbt Cloud only, no CLI)

{
  "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}"
      }
    }
  }
}

---

Where to put the configuration

Claude Code (primary Wire tool)

Option A — Project-specific (recommended for Wire projects, shareable with team): Add to .mcp.json at the repo root. Wire Studio already creates .mcp.json with Atlassian, Fathom, and Context7 servers — merge the dbt entry rather than replacing:

{
  "mcpServers": {
    "atlassian": { ... },
    "fathom": { ... },
    "context7": { ... },
    "dbt": {
      "command": "uvx",
      "args": ["dbt-mcp"],
      "env": {
        "DBT_PROJECT_DIR": "/path/to/project",
        "DBT_PATH": "/path/to/dbt"
      }
    }
  }
}

If using token auth, use ${DBT_TOKEN} references (not literal values) so .mcp.json is safe to commit.

Option B — User-global (your machine only):

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

Option C — Project-scoped via CLI:

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

Claude Desktop

1. Open Claude menu (system menu bar, not in-app) → Settings → Developer → Edit Config
2. Add the JSON configuration
3. Save and restart Claude Desktop
4. Verify: look for the MCP server indicator in the input box bottom-right

Config location:

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

---

Credential security

• Always use env var references (${DBT_TOKEN}) in config files that may be committed
• Never log or display token values in terminal output
• Use .env files with .gitignore for local development; use Secret Manager or env var injection in CI/CD
• Minimum required permissions: read-only for Discovery/Semantic Layer; write permissions only if Admin API or dbt CLI job triggering is needed

---

Verification

Test the local server before configuring a client:

export DBT_PROJECT_DIR=/path/to/project
export DBT_PATH=/path/to/dbt
uvx dbt-mcp
# No errors = server starts successfully; Ctrl+C to stop

After setting up in Claude Code, ask Claude:

• "What dbt tools do you have access to?"
• "List my dbt models" (tests Discovery API)
• "List my dbt metrics" (tests Semantic Layer — requires dbt Cloud connection)

---

Wire Project Notes

• Wire projects default to BigQuery. Set DBT_PROJECT_DIR to the repo root (where dbt_project.yml lives, typically the repo root for Wire projects)
• Wire's .mcp.json already exists — always add the dbt server entry rather than creating a new file
• If using Wire's Dagster orchestration, the dbt MCP server and Dagster skill complement each other: dbt MCP for model development, Dagster skill for orchestration setup
• For projects using dbt Cloud jobs (orchestration tool = dbt_cloud), the remote server gives Claude visibility into job status via the Admin API