Can my agent check the status of a specific Databricks job run?

Yes. Provide the 'job_id' to the 'list_job_runs' tool. The agent will retrieve the chronological history of executions, allowing you to identify successful completions or precise points of failure in your workflows.

How do I explore schemas within a specific Unity Catalog via chat?

Use the 'list_schemas' tool and provide the catalog name. Your agent will pull the detailed databases and schemas registered inside that Unity Catalog, giving you immediate visibility into your data hierarchy.

Can I monitor the health of my Databricks clusters through the agent?

Absolutely. The 'list_clusters' and 'get_cluster' tools allow your agent to retrieve detailed node information and operational statuses, helping you audit cluster health and capacity across your workspace.

Databricks MCP Server for Google ADK 8 tools — connect in under 2 minutes

Name: Databricks
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 8 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Databricks as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="databricks_agent",
    instruction=(
        "You help users interact with Databricks "
        "using 8 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Databricks MCP Server

Connect your Databricks workspace to any AI agent and take full control of your data intelligence platform and lakehouse orchestration through natural conversation.

Google ADK natively supports Databricks as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Cluster Monitoring — List all compute nodes and retrieve detailed information for specific clusters to audit health and capacity limits
Job Orchestration — List all configured workflows and jobs, and monitor recent executions to verify data pipeline statuses
SQL Warehouse Management — Enumerate explicitly configured SQL Serverless warehouses and track their active operational boundaries
Unity Catalog Exploration — List root catalogs and detailed schemas/databases to identify exactly where your structured data resides
Identity Oversight — Fetch profile information for the authenticated user or service principal to verify active workspace permissions
Run Auditing — Retrieve chronological logs of job runs to identify precise points of failure in your complex data workflows

The Databricks MCP Server exposes 8 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Databricks to Google ADK via MCP

Follow these steps to integrate the Databricks MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 8 tools from Databricks via MCP

Why Use Google ADK with the Databricks MCP Server

Google ADK provides unique advantages when paired with Databricks through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Databricks

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Databricks tools with BigQuery, Vertex AI, and Cloud Functions

Databricks + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Databricks MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Databricks and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Databricks tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Databricks regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Databricks

Databricks MCP Tools for Google ADK (8)

These 8 tools become available when you connect Databricks to Google ADK via MCP:

get_cluster

Get cluster details from Databricks

get_me

Get current user from Databricks

list_catalogs

List Unity Catalog catalogs from Databricks

list_clusters

List all clusters from Databricks

list_job_runs

List job runs from Databricks

list_jobs

List all jobs from Databricks

list_schemas

List schemas in catalog from Databricks

list_warehouses

List SQL warehouses from Databricks

Example Prompts for Databricks in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Databricks immediately.

"List all compute clusters in my workspace"

"Show me the last 5 runs for job 'Daily-Sales-ETL'"

"List all catalogs in Unity Catalog"

Troubleshooting Databricks MCP Server with Google ADK

Common issues when connecting Databricks to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Databricks + Google ADK FAQ

Common questions about integrating Databricks MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.