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Cloudinary

Use Cloudinary with AI apps and agents through Vercel Connect. Follow a complete setup guide for secure runtime access.

Create Connector
  1. Install the skill

    $ npx skills add vercel/vercel-plugin --skill vercel-connect
  2. Connect to Cloudinary

    $ vercel connect create cloudinary --name acme-cloudinary
  3. Use 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('cloudinary/acme-cloudinary', {
    subject: { type: 'user', id: userId },
    });

Use Cloudinary in apps and agents

Manage, transform, and deliver images and videos.

Why use Vercel Connect with Cloudinary?

  • Credentials on demand

    Request Cloudinary credentials only when your application or agent needs them instead of copying secrets into application code.

  • Access for the right subject

    Request user-authorized Cloudinary access so actions follow the identity and permissions of the person using your application.

  • Centralized credential management

    Manage Cloudinary 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 Cloudinary with your stack

Follow a complete setup for the Connect SDK or a supported agent framework.

Add Cloudinary to an existing Vercel application with the Connect SDK.

  1. Install the Connect SDK

    npm install @vercel/connect
  2. Create the Cloudinary connector

    Run these commands from the project that will use the connection.

    vercel link
    vercel connect create cloudinary --name acme-cloudinary
    vercel env pull
  3. Request Cloudinary credentials

    app/api/route.ts
    import { getToken } from '@vercel/connect';
    const userId = 'user_123';
    const token = await getToken('cloudinary/acme-cloudinary', {
    subject: { type: 'user', id: userId },
    });
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