Databricks MCP Interface Adapter

This component functions as an MCP server endpoint, establishing a bidirectional communication channel with the Databricks REST API. This capability allows Language Models to programmatically issue data manipulation/query commands, inspect the catalog of defined data pipelines (jobs), and obtain real-time status updates for those computations.

Core Functionalities

• Execute arbitrary SQL statements against designated Databricks SQL computing endpoints.
• Generate a comprehensive manifest of all scheduled and ad-hoc Databricks workflows.
• Query the precise execution status associated with any given Databricks job identifier.
• Fetch exhaustive metadata pertaining to a specified Databricks job execution.

System Requirements

• Requires Python interpreter version 3.7 or newer.
• Access to a configured Databricks environment, necessitating:
  • A valid Personal Access Token (PAT).
  • The network address and identifier for an active SQL endpoint/warehouse.
  • Appropriate IAM permissions to initiate queries and enumerate job resources.

Deployment Procedure

1. Clone the source code repository.

2. Establish and activate an isolated Python environment (highly recommended):

   python -m venv .venv source .venv/bin/activate # Use .venv\Scripts\activate on Windows OS

3. Install required library dependencies:

   pip install -r requirements.txt

4. Populate the configuration file named .env in the project root with the following essential environment variables:

   DATABRICKS_HOST=your-databricks-instance.cloud.databricks.com DATABRICKS_TOKEN=your-personal-access-token DATABRICKS_HTTP_PATH=/sql/1.0/warehouses/your-warehouse-id

5. (Optional, yet advised) Validate network connectivity and credential integrity:

   python test_connection.py

Credential Acquisition Guidance

1. Workspace Hostname: Provide the root URL of your Databricks deployment (e.g., mycompany.cloud.databricks.com).
2. Access Token: Generate a PAT within the Databricks UI:
   • Navigate to User Settings (top-right profile menu).
   • Select the 'Developer' pane.
   • Under the 'Access tokens' heading, click 'Manage'.
   • Generate a fresh token and secure its value immediately upon creation.
3. Warehouse HTTP Path: Locate this path within the SQL Warehouses management section:
   • Select the target SQL Endpoint.
   • Examine the connection details pane to retrieve the required HTTP Path string.

Initiating the Service

Launch the MCP server application:

python main.py

Verification of server responsiveness can be performed using the official MCP inspection utility:

npx @modelcontextprotocol/inspector python3 main.py

Exposed MCP Interface Functions

The following methods are registered and callable by compliant LLM agents:

1. execute_sql(query_string: str) - Submits and runs a declarative query against the operational SQL compute cluster.
2. enumerate_workflows() - Fetches a list of all defined automated tasks (jobs) within the Databricks environment.
3. check_workflow_status(identifier: int) - Retrieves the current state (e.g., RUNNING, SUCCESS, FAILED) for a job identified by its unique ID.
4. fetch_workflow_metadata(identifier: int) - Returns comprehensive configuration and historical run data for a specified job ID.

Contextual Integration Examples (LLM Interaction)

When coupled with an LLM supporting the MCP specification, this gateway enables sophisticated data interaction via natural prose:

• "What schemas are accessible via the default catalog?"
• "Generate a count of entries in the 'transaction_logs' table."
• "Provide a full inventory of all configured ETL pipelines."
• "Determine if workflow ID 123 has finished execution."
• "Display the parameters used for the pipeline identified as #456."

Diagnostics and Problem Resolution

Connectivity Faults

• Confirm the host value omits scheme prefixes like http://.
• Ensure the target SQL warehouse cluster is presently active and not paused.
• Validate the PAT possesses the minimal necessary scope permissions.
• Re-run the integrated validation script: python test_connection.py

Security Posture Notes

• The Databricks PAT grants high-level access; treat it as a critical secret.
• The .env file must be excluded from any source control repositories (e.g., Git).
• Implement least-privilege principles when defining the token's operational scope.
• Deploy this adapter within a hardened, access-controlled network segment.