How to Use the Databricks MCP in Claude Code

Q: How do I add Databricks to Claude Code?

Run the command claude mcp add followed by the server URL in your terminal. Ensure your flags are placed before the server name.

Run Databricks MCP Server tasks from your terminal with Claude Code.

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Connect Databricks MCP to Claude Code

Create your Vinkius account to connect Databricks to Claude Code and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Databricks with Claude Code

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Claude Code tracks Databricks job status

Use `list_job_runs` to pipe output directly into your terminal scripts. Claude Code grabs the data and formats it for your CI/CD pipeline. You get instant feedback on job health without opening a browser. It makes monitoring large-scale operations simple and fast.

Query Databricks infrastructure with Claude Code

Run `get_me` or `list_clusters` as part of your shell workflow. Claude Code returns the output as JSON that you can filter using standard CLI tools. This gives you programmatic control over your compute resources. It is built for DevOps engineers who prefer the terminal over a GUI.

Map Unity Catalog via Claude Code

Automate your data discovery by calling `list_catalogs` from your command line. Claude Code fetches the structure so you can feed it into your next script. It removes the need for manual navigation. You define the logic and the server provides the data on demand.

Setup guide

Set up Databricks MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see databricks-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest Databricks transactions." It will automatically discover and invoke the available Databricks tools.

Terminal

claude mcp add --transport http databricks-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

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Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the Databricks MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "databricks-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Databricks. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Databricks MCP in Claude Code

Run the command `claude mcp add` followed by the server URL in your terminal. Ensure your flags are placed before the server name.

Absolutely. Since it runs in the terminal, you can script your Databricks checks into any cron job or deployment pipeline.

Yes. The server supports various transports including HTTP and stdio, making it perfect for containerized environments.

No. The interaction stays within your terminal session. Claude Code processes the tool output in memory and doesn't write your lakehouse info to disk.

The server uses a zero-trust model. Every request is scoped to your endpoint token and ephemeral, so your lakehouse schema remains isolated.

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