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Connect Databricks to Claude Code

Let Claude run governed reads and writes against your Databricks lakehouse. From the terminal, inside the sessions where you already work.

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How do you connect Databricks to Claude Code?

Claude Code reaches outside tools through MCP servers. To connect Databricks, you add a Databricks MCP server: a small hosted service that exposes Databricks's data and actions over the Model Context Protocol. With a custom connector we build for you, that is one command in the terminal, then an OAuth sign-in with your own Databricks account. No API keys pasted into config files.

claude mcp add --transport http databricks https://your-connector-url/mcp

Then run /mcp inside a Claude Code session to sign in. Add it with --scope project and the connector is checked into the repo for your whole team.

What can Claude Code do in Databricks once connected?

Full read-write Databricks access lets Claude run governed inserts and updates, create or alter tables in Unity Catalog, trigger jobs and pipelines, and manage warehouses, all behind your approval. The analysis that used to end at a SELECT can now apply the change where the data already lives.

  • Run a parameterized INSERT or MERGE into a target Delta table after you approve it
  • Create or alter a table or schema in Unity Catalog
  • Trigger a job run or workflow and report back when it finishes
  • Start, stop, or resize a SQL warehouse to match the workload
  • Grant or revoke a scoped permission on a catalog object
  • Update or tag table metadata to keep the catalog accurate

One connector, every Claude surface

The connector we build is a remote MCP server, which is the same standard claude.ai and Claude Desktop use. Add it once and the same Databricks access works in Claude Code for you, in claude.ai for the rest of the team, and in Claude Desktop. One build, one set of permissions, one monthly plan covering all of them.

Build it yourself, or have it built?

If you live in the terminal, you can absolutely write your own MCP server against the Databricks API. The protocol is open. What you take on is everything around the happy path: OAuth token refresh, hosting, monitoring, keeping up when Databricks changes its API and when the MCP spec itself moves, and scoping write actions so an agent can never do more than you intended. We build Databricks connectors with separated read and write tools and approval gates on destructive actions, then host and maintain them so they keep working while you work.

Frequently asked questions

Does the same Databricks connector work in claude.ai and Claude Code?
Yes. It is one remote MCP server. Claude Code adds it with a single "claude mcp add" command; claude.ai and Claude Desktop add it as a custom connector in Settings. Each person signs in with their own Databricks account, so access always matches what that person can already see and do.
Do I need to host or maintain anything myself?
No. The connector runs as a hosted service we operate: we handle uptime, token health, API changes on Databricks's side, and MCP spec migrations under the monthly plan. Your side is one command in the terminal and an OAuth sign-in.
Is it safe to give a coding agent write access to Databricks?
Write access is scoped, not blanket. Read tools and write tools are separated, destructive actions like deleting or sending are gated behind your explicit approval, and the connector can never exceed the permissions of the Databricks account it signs in with. Revoking access is one click in Databricks.

More on the Databricks connector

Databricks connector for claude.aiSnowflake + Claude CodeBigQuery + Claude CodePostgreSQL + Claude Code

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