How to Use the Luma AI (Generative Video & Creative) MCP in Vercel AI SDK

Q: How do I handle long-running video generations in Vercel AI SDK with the Luma AI (Generative Video & Creative) MCP Server?

You start the generation using lm.texttovideo and immediately return the queued state to the client. Then, set up a polling loop using lm.getgeneration on your serverless route to update the UI as soon as the video URL becomes available.

Q: Can I use Luma AI (Generative Video & Creative) to animate static images inside a Vercel AI SDK project?

Yes. You pass the image URL to lm.imagetovideo through the SDK's tool calling mechanism. The model uses that image as the first frame to generate a coherent video sequence.

Q: What is the cleanest way to check generation credits in Vercel AI SDK using the Luma AI (Generative Video & Creative) server?

Call lm.getcredits before executing any generation tools. This lets you display the user's balance in your React components and disable the generation buttons if the account runs out of credits.

Q: How do I clean up completed video files from my account?

Use lm.deletegeneration with the specific generation ID. This removes the video asset and its associated data from the Luma platform instantly.

Build real-time video generation interfaces that stream Luma AI outputs directly into your Next.js frontend with Vercel AI SDK.

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Connect Luma AI (Generative Video & Creative) MCP to Vercel AI SDK

Create your Vinkius account to connect Luma AI (Generative Video & Creative) 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 Luma AI (Generative Video & Creative) with Vercel AI SDK

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Direct UI Streaming with Vercel AI SDK

`lm.text_to_video` starts the generation process on Luma's servers, and this MCP Server lets you feed that state directly to your user's browser. Instead of making users wait on a blank screen, your Next.js app receives the initial generation payload immediately, showing the queued state in real-time. You poll the status using `lm.get_generation` inside an Edge Function, updating the UI as the video progresses from dreaming to completed. The SDK streams these status updates and the final video URL without blocking the main thread.

On-Demand Camera Work and Motion Control

`lm.camera_control` lets your client specify camera movements like pan, tilt, orbit, or dolly through simple prompt instructions. Your application parses user UI actions, translates them into spatial coordinates, and triggers the video generation instantly. You can also use `lm.image_to_video` to set the starting frame of these camera moves. The Vercel AI SDK manages the payload transfer, ensuring the input image and camera vectors reach the Luma API without timeout failures.

Credit Auditing and Asset Management

`lm.get_credits` checks your remaining Dream Machine balance before you trigger a heavy video generation loop. This prevents failed API errors from reaching your users by letting your code block requests when credits run low. Users can also clean up their workspace using `lm.delete_generation` directly from your custom dashboard. The MCP Server handles the lightweight HTTP transport for these quick administrative tasks, keeping your app fast and responsive.

Setup guide

Set up Luma AI (Generative Video & Creative) 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 Luma AI (Generative Video & Creative) 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 Luma AI (Generative Video & Creative) 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 Luma 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 Luma AI (Generative Video & Creative) MCP in Vercel AI SDK

You start the generation using `lm.text_to_video` and immediately return the queued state to the client. Then, set up a polling loop using `lm.get_generation` on your serverless route to update the UI as soon as the video URL becomes available.

Yes. You pass the image URL to `lm.image_to_video` through the SDK's tool calling mechanism. The model uses that image as the first frame to generate a coherent video sequence.

Call `lm.get_credits` before executing any generation tools. This lets you display the user's balance in your React components and disable the generation buttons if the account runs out of credits.

Use `lm.delete_generation` with the specific generation ID. This removes the video asset and its associated data from the Luma platform instantly.

Your Luma API keys and prompt text strings are never stored on Vinkius. They pass through an ephemeral, zero-trust V8 sandbox that destroys the container as soon as the API call completes, leaving no logs of your generated video URLs.

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