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 AutoGen 8 tools — connect in under 2 minutes

Name: Databricks
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 8 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Databricks as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.

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

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="databricks_agent",
            tools=tools,
            system_message=(
                "You help users with Databricks. "
                "8 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Databricks tools. Connect 8 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

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 AutoGen 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 AutoGen via MCP

Follow these steps to integrate the Databricks MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 8 tools from Databricks automatically

Why Use AutoGen with the Databricks MCP Server

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

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Databricks tools to solve complex tasks

Role-based architecture lets you assign Databricks tool access to specific agents — a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Databricks tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Databricks tool responses in an isolated environment

Databricks + AutoGen Use Cases

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

Collaborative analysis: one agent queries Databricks while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Databricks, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Databricks data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Databricks responses in a sandboxed execution environment

Databricks MCP Tools for AutoGen (8)

These 8 tools become available when you connect Databricks to AutoGen 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 AutoGen

Ready-to-use prompts you can give your AutoGen 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 AutoGen

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

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Databricks + AutoGen FAQ

Common questions about integrating Databricks MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Databricks tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.