How to Use the Vadoo AI MCP in Vercel AI SDK

Q: How do I check the status of Vadoo AI videos in my Next.js app?

You call vadooaicheckgenerationstatus and stream that response into your UI. The client handles the status checks in real-time, showing users exactly where the video generation is.

Q: What if I need to generate captions using Vadoo AI and display them live?

Just call vadooaigeneratecaption. Because this MCP Server supports streaming, you'll see the generated text appear in your user interface immediately, without waiting for a single chunk of data.

Q: Can Vercel AI SDK handle complex video workflows from Vadoo AI?

Yes. You can chain calls like generating the video with vadooaigeneratevideo, and then calling vadooaicreateclips immediately after, all while streaming progress back to your users.

Q: Does Vadoo AI require specific authentication when using the Vercel AI SDK?

The client supports an authProvider, so you can handle OAuth or other forms of authentication before interacting with the MCP Server tools.

See Vadoo AI results stream live in your Next.js app using the Vercel AI SDK.

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Connect Vadoo AI MCP to Vercel AI SDK

Create your Vinkius account to connect Vadoo 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 Vadoo AI with Vercel AI SDK

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Generate video content, streaming updates instantly.

When you call `vadooai_generate_video`, the client streams progress back to the UI as it happens. You don't wait for a final response; you see the generation process unfold live in your front-end product. This real-time feedback is crucial for good UX. After generating video, you can call `vadooai_check_generation_status` immediately so users see status updates without needing to poll an endpoint.

Automate captions and podcast creation on the fly.

Need text assets from a video? Use `vadooai_generate_caption` to get accurate captions, or run `vadooai_generate_podcast` to turn existing footage into an AI podcast script. Both tools stream their results directly into your React component. This means the user sees the resulting text appear piece by piece—it feels instant and interactive. The entire MCP Server works with streaming transport, perfect for building responsive client experiences.

Process finished videos into reusable clips.

Once a video is ready, use `vadooai_create_clips` to slice it up automatically. This tool processes the full output and gives you manageable segments that can be displayed in real-time. You can check the final outcome details by calling `vadooai_check_video_status`. The whole process—from creation to clipping—flows through this MCP Server, giving your AI client a solid pipeline for video handling.

Setup guide

Set up Vadoo 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 Vadoo 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 Vadoo AI transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vadoo AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Vadoo AI MCP in Vercel AI SDK

You call `vadooai_check_generation_status` and stream that response into your UI. The client handles the status checks in real-time, showing users exactly where the video generation is.

Just call `vadooai_generate_caption`. Because this MCP Server supports streaming, you'll see the generated text appear in your user interface immediately, without waiting for a single chunk of data.

Yes. You can chain calls like generating the video with `vadooai_generate_video`, and then calling `vadooai_create_clips` immediately after, all while streaming progress back to your users.

The client supports an `authProvider`, so you can handle OAuth or other forms of authentication before interacting with the MCP Server tools.

This server handles video generation requests and associated metadata, including prompt text used for `vadooai_generate_video`.

Use it with your favorite AI tools

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