How to add Databricks MCP Servers to Cursor
Databricks Labs server exposing Unity Catalog functions, vector search indexes and Genie spaces as agent tools. Paste the config into ~/.cursor/mcp.json and restart Cursor.
Last updated June 14, 2026 · 93★ · stdio · oauth · official
Cursor config for Databricks MCP Servers
git clone https://github.com/databrickslabs/mcp && uv --directory ./mcp run unitycatalog-mcp -s your_catalog.your_schema{
"mcpServers": {
"databricks-mcp-servers": {
"command": "/path/to/uv/executable/uv",
"args": [
"--directory",
"/path/to/this/repo",
"run",
"unitycatalog-mcp",
"-s",
"your_catalog.your_schema",
"-g",
"genie_space_id_1,genie_space_id_2"
]
}
}
}Setup steps
- 1Open Cursor → Settings → MCP → Add new MCP server (or edit ~/.cursor/mcp.json directly).
- 2Paste the Databricks MCP Servers config below into the "mcpServers" object.
- 3Fill in placeholder secrets, then save.
- 4Cursor reloads MCP servers automatically — check Settings → MCP for a green status dot.
- 5Ask Cursor to use one of Databricks MCP Servers's tools to confirm it's connected.
Before you start
- uv installed, plus Python 3.12 via `uv python install 3.12`
- Databricks CLI credentials configured with access to the required APIs
- A Unity Catalog schema (and optionally Genie space IDs) the principal can access
- A clone of the databrickslabs/mcp repo — the server runs from source via uv
Security
Unity Catalog permissions are always enforced — an agent can only call functions and query indexes its principal has been granted; credentials come from your local Databricks CLI auth, not the config file. Note the UC server is deprecated in favor of Databricks Managed MCP servers, and Labs projects are provided as-is with no support SLA.
Databricks MCP Servers + Cursor FAQ
Where is the Cursor config file?
Cursor reads MCP servers from ~/.cursor/mcp.json. Paste the Databricks MCP Servers config there under the "mcpServers" key and restart the client.
Is Databricks MCP Servers safe to use with Cursor?
Unity Catalog permissions are always enforced — an agent can only call functions and query indexes its principal has been granted; credentials come from your local Databricks CLI auth, not the config file. Note the UC server is deprecated in favor of Databricks Managed MCP servers, and Labs projects are provided as-is with no support SLA.
Is this the official Databricks MCP server?
It's from Databricks Labs — Databricks' experimental arm — so official but explicitly unsupported (no SLA, as-is). The fully supported path today is Databricks' Managed MCP servers built into the platform; this repo's UC server is the deprecated self-managed predecessor.
Is it safe to point at production data?
Access control stays with Unity Catalog: the server cannot exceed the permissions of the principal it runs as, and Databricks states permissions are always enforced. Scope the -s schema narrowly and run the Apps deployment under a least-privilege service principal.
Do I have to deploy anything to my workspace?
No — local stdio use only needs uv, a repo clone, and your CLI credentials. The Databricks Apps deployment is optional, for sharing one server across users or connecting remote clients over HTTP.