databricks-mcp

databricks-mcp

Exposes Databricks REST APIs as MCP tools for managing and querying a Databricks workspace, including clusters, jobs, SQL, Unity Catalog, and more.

Category
访问服务器

README

databricks-mcp

A Model Context Protocol (MCP) server that exposes the Databricks REST APIs as MCP tools so an LLM agent can manage and query a Databricks workspace.

The server speaks MCP over stdio (for Claude Desktop / Claude Code / Cursor / IDE hosts) and supports a single --transport streamable-http mode for remote deployments (Databricks Apps, container, etc.).

Features

Domain Tools
Workspace list / get / create / delete / export / import notebooks; list / get / mkdir / delete workspace files and dirs
Clusters list, get, create, start, terminate, restart, resize, edit, delete; cluster events; cluster policies; instance pools; node types; spark versions
Jobs list, get, create, run-now, run-now-and-wait, list-runs, get-run, cancel-run, delete; full task types (notebook, spark_jar, python_wheel, dbt, sql, pipeline, run_job, condition, for_each)
SQL Warehouses list, get, create, start, stop, edit, delete
SQL Queries / Dashboards / Alerts / Data list / get / run SQL statements, dashboards (legacy + Lakeview), alerts
Unity Catalog catalogs, schemas, tables, columns, volumes, functions, grants
Delta Live Tables (Pipelines) list, get, create, start, stop, delete; pipeline updates
MLflow experiments, runs, models, registered models, model versions, webhooks
Model Serving serving endpoints (create, list, get, update, delete, query)
Vector Search endpoints (create, list, get, delete), indexes (create, list, get, delete, upsert, query, scan)
Databricks Apps list, get, create, update, delete
Repos (Git) list, get, create, update, delete; pull, push, commit
Secrets list, put, get, delete scopes and secrets
DBFS list, get, put, delete files
Tokens list, create, revoke
Permissions get / set / update / delete ACLs on jobs, clusters, pipelines, etc.
Identity / SCIM list users, groups, service principals
Delta Sharing list / create / update / delete shares, recipients, providers
Genie (AI/BI) list spaces, ask-question
Utilities workspace status, current user, whoami

Install

# From source (this repo)
uv tool install .

# Or pipx / pip
pipx install .
# or
pip install .

# Or run directly with uvx
uvx --from . databricks-mcp

Configure

The server needs three environment variables (or CLI flags):

Variable Required Example
DATABRICKS_HOST yes https://dbc-1234567890.cloud.databricks.com
DATABRICKS_TOKEN one of PAT or OAuth must be set dapi... (Personal Access Token)
DATABRICKS_CLIENT_ID + DATABRICKS_CLIENT_SECRET OAuth M2M alternative to PAT
DATABRICKS_ACCOUNT_ID only for account-level APIs 1234567890

You can also pass them as CLI flags: --host, --token.

Use with Claude Desktop

Add this to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "databricks": {
      "command": "databricks-mcp",
      "env": {
        "DATABRICKS_HOST": "https://dbc-1234567890.cloud.databricks.com",
        "DATABRICKS_TOKEN": "dapi..."
      }
    }
  }
}

Use with Claude Code

claude mcp add databricks \
  --transport stdio \
  --env DATABRICKS_HOST=https://dbc-1234567890.cloud.databricks.com \
  --env DATABRICKS_TOKEN=dapi... \
  -- databricks-mcp

Run from source

# stdio (default)
uv run databricks-mcp

# streamable HTTP (for remote deployment / Databricks Apps)
uv run databricks-mcp --transport streamable-http --host 0.0.0.0 --port 8000

Test with MCP Inspector

npx -y @modelcontextprotocol/inspector databricks-mcp

Then set DATABRICKS_HOST and DATABRICKS_TOKEN in the Inspector's env form and click Connect. Browse the tool list and try whoami first.

License

MIT.

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