Tabfleet
Use Tabfleet 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
Tabfleet$ vercel connect create tabfleet --name acme-tabfleetUse 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('tabfleet/acme-tabfleet', {subject: { type: 'user', id: userId },});
Use Tabfleet in apps and agents
Run isolated cloud browsers for AI agents.
Read the Tabfleet developer docs(opens in new tab)Why use Vercel Connect with Tabfleet?
Credentials on demand
Request Tabfleet credentials only when your application or agent needs them instead of copying secrets into application code.
Access for the right subject
Support both user-authorized and app-scoped Tabfleet access from the same connection layer.
Managed authorization lifecycle
Centralize Tabfleet 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 Tabfleet with your stack
Follow a complete setup for the Connect SDK or a supported agent framework.
Add Tabfleet to an existing Vercel application with the Connect SDK.
Install the Connect SDK
npm install @vercel/connectCreate the Tabfleet connector
Run these commands from the project that will use the connection.
vercel linkvercel connect create tabfleet --name acme-tabfleetvercel env pullRequest Tabfleet credentials
app/api/route.tsimport { getToken } from '@vercel/connect';const userId = 'user_123';const token = await getToken('tabfleet/acme-tabfleet', {subject: { type: 'user', id: userId },});