How to Use the Creatomate MCP in Vercel AI SDK

Q: How does the Vercel AI SDK handle long-running Creatomate video renders?

It uses non-blocking polling. The SDK calls rendervideo to kick off the job, then periodically checks getrenderstatus to update your UI state while streaming other text responses.

Q: Can I use the Vercel AI SDK to search Creatomate templates dynamically?

Yes. Your agent can call searchtemplatesbyname based on user input and show the matching video templates directly in the chat stream.

Q: How do I handle audio and image assets when rendering?

Use listmediaassets to find existing files, or pass public URLs directly into the modifications object when calling rendervideo.

Pipe live video rendering tasks directly into your React UI with the Vercel AI SDK and this Creatomate MCP Server.

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Connect Creatomate MCP to Vercel AI SDK

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

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Real-time video rendering status in your Vercel AI SDK UI

Your Next.js frontend gets live updates on video generation tasks by calling `get_render_status` directly from the user's viewport. This keeps the interface snappy because your AI client pulls real-time progress percentages instead of waiting for a full reload. Instead of waiting for a backend webhook, the client handles the polling loop in the background. It grabs the finished video URL from `get_render_status` the second it's ready, letting your React components render the video player instantly.

Interactive template customization

Let your users modify video layouts on the fly using `get_template_details` to inspect the video structure. Your agent reads the available text fields and image placeholders, then presents them as options in the chat. Next, the agent calls `render_video` with the user's custom text and assets. The streaming interface displays the new video options as they generate, turning a static template into an interactive design canvas.

Direct media asset browsing

No more blind uploads when your frontend agent uses `list_media_assets` via the MCP to show users what images, audio tracks, and clips they have stored in their project. This lets users browse their library directly inside the chat interface. Once they pick an asset, your agent feeds that ID straight into `render_video`. It keeps the entire assets workflow inside the live chat UI without forcing users to open a separate media manager.

Setup guide

Set up Creatomate 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 Creatomate 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 Creatomate 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 Creatomate. 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 Creatomate MCP in Vercel AI SDK

It uses non-blocking polling. The SDK calls `render_video` to kick off the job, then periodically checks `get_render_status` to update your UI state while streaming other text responses.

Yes. Your agent can call `search_templates_by_name` based on user input and show the matching video templates directly in the chat stream.

No. You can initialize the MCP client inside your Next.js Edge Route or Server Action and pass the tools directly to `streamText`.

Use `list_media_assets` to find existing files, or pass public URLs directly into the modifications object when calling `render_video`.

Yes. All project metadata and video files remain isolated within Vinkius's secure sandboxed environment. Your API keys are never exposed to the client side, and temporary render URLs are only accessed via secure, authenticated HTTP requests.

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