Data · MODEL CONTEXT PROTOCOL
mcp-databricks-server
MCP Server for Databricks
WHAT IT CONNECTS
What mcp-databricks-server gives an AI Agent
- Run SQL queries on Databricks SQL warehouses
- List all Databricks jobs
- Get status of specific Databricks jobs
- Get detailed information about Databricks jobs
- Python 3.7+
- Databricks workspace with:
- Personal access token
- SQL warehouse endpoint
- Permissions to run queries and access jobs
- Clone this repository
- Create and activate a virtual environment (recommended):
- Install dependencies:
- Create a `.env` file in the root directory with the following variables:
- Test your connection (optional but recommended):
- **Host**: Your Databricks instance URL (e.g., `your-instance.cloud.databricks.com`)
- **Token**: Create a personal access token in Databricks:
- Go to User Settings (click your username in the top right)
- Select "Developer" tab
- Click "Manage" under "Access tokens"
- Generate a new token, and save it immediately
- **HTTP Path**: For your SQL warehouse:
- Go to SQL Warehouses in Databricks
- Select your warehouse
- Find the connection details and copy the HTTP Path
- **run_sql_query(sql: str)** - Execute SQL queries on your Databricks SQL warehouse
- **list_jobs()** - List all Databricks jobs in your workspace
- **get_job_status(job_id: int)** - Get the status of a specific Databricks job by ID
- **get_job_details(job_id: int)** - Get detailed information about a specific Databricks job
- "Show me all tables in the database"
- "Run a query to count records in the customer table"
- "List all my Databricks jobs"
- "Check the status of job #123"
- "Show me details about job #456"
- Ensure your Databricks host is correct and doesn't include `https://` prefix
- Check that your SQL warehouse is running and accessible
- Verify your personal access token has the necessary permissions
- Run the included test script: `python test_connection.py`
- Your Databricks personal access token provides direct access to your workspace
- Secure your `.env` file and never commit it to version control
- Consider using Databricks token with appropriate permission scopes only
- Run this server in a secure environment
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.