TextRazor
Use TextRazor 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
Use its data in agents(opens in new tab) and apps(opens in new tab)
import { getToken } from '@vercel/connect';const token = await getToken('textrazor/acme-textrazor');
Use TextRazor in apps and agents
Extract entities, relationships, and meaning from text.
Why use Vercel Connect with TextRazor?
Credentials on demand
Request TextRazor credentials only when your application or agent needs them instead of copying secrets into application code.
Access for the right subject
Keep app-scoped TextRazor access behind a reusable connector controlled by your team.
Centralized credential management
Manage TextRazor credentials in one place and retrieve them through a consistent runtime API.
Vercel-native controls
Bind connections to the projects and environments that need them while Vercel OIDC authenticates each runtime request.
Use TextRazor with your stack
Follow a complete setup for the Connect SDK or a supported agent framework.
Add TextRazor to an existing Vercel application with the Connect SDK.
Install the Connect SDK
npm install @vercel/connectCreate the TextRazor connector
Run these commands from the project that will use the connection.
vercel linkvercel connect create textrazor --name acme-textrazorvercel env pullRequest TextRazor credentials
app/api/route.tsimport { getToken } from '@vercel/connect';const token = await getToken('textrazor/acme-textrazor');
