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Keiki

Use Keiki 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 Keiki

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

Use Keiki in apps and agents

Put your agent on iMessage, Teams, Slack, and email.

Read the Keiki developer docs(opens in new tab)

Why use Vercel Connect with Keiki?

  • Credentials on demand

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

  • Access for the right subject

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

  • Managed authorization lifecycle

    Centralize Keiki 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 Keiki with your stack

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

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

  1. Install the Connect SDK

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

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

    vercel link
    vercel connect create keiki --name acme-keiki
    vercel env pull
  3. Request Keiki credentials

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