How to Use the GAN.ai MCP in Vercel AI SDK

Q: How do I check my video history using GAN.ai in the Vercel AI SDK?

Call listgeneratedvideos via your MCP client. This returns a list of your previous renders which you can then map over in your UI.

Stream personalized video data directly into your Vercel AI SDK interface for real-time user feedback.

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Connect GAN.ai MCP to Vercel AI SDK

Create your Vinkius account to connect GAN.ai to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup GAN.ai with Vercel AI SDK

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Generate personalized video assets

Feed your UI with live video generation by calling `generate_personalized_videos` directly within your Edge Functions. Your front-end receives the output as it happens, removing the need for clunky loading states. Use `generate_single_video` for individual requests when a user triggers a specific action in your Next.js app. This keeps your interface snappy and responsive, letting the user see exactly what the agent is doing at any moment.

Monitor generation status via MCP Server

Track background processes by polling `get_generation_status` to update your React components in real-time. You'll know exactly when a file is ready for playback without refreshing the page. Verify your backend handshake using `verify_api_connection` during your app's initialization. This prevents runtime errors and ensures your Vercel deployment has active access to the video rendering pipeline.

Query workspace and template metadata

Access your project schemas and landing pages by calling `get_project_metadata` and `list_landing_templates`. This allows your AI to dynamically suggest templates based on the user's specific input. Retrieve aggregate performance metrics through `get_video_stats` to display engagement charts directly in your dashboard. You can pull your entire workspace configuration with `get_workspace_info` to ensure your agent has context on all active projects.

Setup guide

Set up GAN.ai MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all GAN.ai tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent GAN.ai transactions",
});

console.log(text);
await mcpClient.close();

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Common questions about GAN.ai MCP in Vercel AI SDK

Install the package and initialize the client using the provided URL. You then pass the tools to your streamText or generateText functions to make them available to your agent.

Yes, you can trigger batch jobs using the tools provided. The SDK handles the streaming response so you can manage the feedback loop in your frontend as videos finish.

It does. The MCP integration is designed for lightweight transport, making it compatible with Edge Functions and serverless environments.

Call `list_generated_videos` via your MCP client. This returns a list of your previous renders which you can then map over in your UI.

All video metadata and generation requests stay within your authenticated session. We only process the specific parameters you send through the authorized endpoint.

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