Databricks
Use Databricks with AI apps and agents through Vercel Connect. Follow a complete setup guide for secure runtime access.
Install the skill
$ npx skills add vercel/vercel-plugin --skill vercel-connectConnect to
Databricks$ vercel connect create databricks --name acme-databricksUse its data in agents(opens in new tab) and apps(opens in new tab)
import { getToken } from '@vercel/connect';const userId = 'user_123';const token = await getToken('databricks/acme-databricks', {subject: { type: 'user', id: userId },});
Use Databricks in apps and agents
Query lakehouse data and manage analytics workloads.
Why use Vercel Connect with Databricks?
Credentials on demand
Request Databricks credentials only when your application or agent needs them instead of copying secrets into application code.
Access for the right subject
Request user-authorized Databricks access so actions follow the identity and permissions of the person using your application.
Managed authorization lifecycle
Centralize Databricks authorization and token exchange rather than rebuilding the provider flow in every application.
Vercel-native controls
Bind connections to the projects and environments that need them while Vercel OIDC authenticates each runtime request.
Use Databricks with your stack
Follow a complete setup for the Connect SDK or a supported agent framework.
Add Databricks to an existing Vercel application with the Connect SDK.
Install the Connect SDK
npm install @vercel/connectCreate the Databricks connector
Run these commands from the project that will use the connection.
vercel linkvercel connect create databricks --name acme-databricksvercel env pullRequest Databricks credentials
app/api/route.tsimport { getToken } from '@vercel/connect';const userId = 'user_123';const token = await getToken('databricks/acme-databricks', {subject: { type: 'user', id: userId },});