Databricks MCP Server
Manage lakehouse via Databricks — monitor compute clusters, track job executions, audit SQL warehouses, and explore Unity Catalog directly from any AI agent.
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What is the Databricks MCP Server?
The Databricks MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Databricks via 8 tools. Manage lakehouse via Databricks — monitor compute clusters, track job executions, audit SQL warehouses, and explore Unity Catalog directly from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (8)
Tools for your AI Agents to operate Databricks
Ask your AI agent "List all compute clusters in my workspace" and get the answer without opening a single dashboard. With 8 tools connected to real Databricks data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Databricks MCP Server capabilities
8 toolsGet cluster details from Databricks
Get current user from Databricks
List Unity Catalog catalogs from Databricks
List all clusters from Databricks
List job runs from Databricks
List all jobs from Databricks
List schemas in catalog from Databricks
List SQL warehouses from Databricks
What the Databricks MCP Server unlocks
Connect your Databricks workspace to any AI agent and take full control of your data intelligence platform and lakehouse orchestration through natural conversation.
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
How it works
1. Subscribe to this server
2. Enter your Databricks Host URL and Personal Access Token (PAT)
3. Start managing your lakehouse from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Data Engineers — monitor job runs and cluster health without leaving the development environment
- Analytics Engineers — explore Unity Catalog schemas and verify SQL warehouse availability in real-time
- Data Platform Teams — audit workspace resources and monitor active service principal identities
- MLOps Engineers — track model training jobs and verify compute cluster configurations through natural language
Frequently asked questions about the Databricks MCP Server
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.
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Connect Databricks with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of Databricks MCP Server
Production-grade Databricks MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.