How to Use the Gumlet MCP in Vercel AI SDK

Q: Can the Vercel AI SDK handle Gumlet video uploads directly?

Yes, you use the createvideoupload tool. The client initiates the request and you handle the binary stream within your standard app flow.

Q: How do I check my Gumlet usage limits in Vercel AI SDK?

Call getaccountinfo from your agent. It returns your current plan details and usage metrics so you can build logic around your remaining quota.

Q: Does this MCP server support real-time Gumlet webhook monitoring?

You can use listwebhooks to inspect your current configuration. This lets your AI client verify that your events are correctly registered.

Stream Gumlet media data straight into your UI with the Vercel AI SDK. Build interfaces that update as your agent works.

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Connect Gumlet MCP to Vercel AI SDK

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

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Real-time media asset management

Feed your UI live status updates by connecting your app to `list_videos` and `list_video_collections`. Your agent pulls the latest data directly into your state management layer without extra API boilerplate. Displaying your library becomes a matter of rendering the tool output. Use `get_video_details` to verify processing status before your users see the final stream.

Automated video and image orchestration

Trigger uploads and updates programmatically using `create_video_upload` or `update_video_thumbnail`. Your AI client handles the heavy lifting, allowing you to focus on the user experience rather than backend piping. Everything stays in sync because tool results flow directly into your app logic. When you need to swap an image or change a thumbnail, the command propagates instantly.

Actionable CDN analytics in-app

Get deep performance insights by parsing `get_video_analytics` results within your edge functions. Your AI client turns raw CDN logs into readable data points that you can chart for your end users. Monitor your account health through `get_account_info` to ensure your delivery limits aren't hit. It's a clean way to keep your metrics visible without leaving the development environment.

Setup guide

Set up Gumlet 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 Gumlet 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 Gumlet transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Gumlet. 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.

Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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place for every integration

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Common questions about Gumlet MCP in Vercel AI SDK

Install the MCP client via npm and point it to the Vinkius endpoint. You then register the tools with your AI client instance to start executing functions.

Yes, you use the `create_video_upload` tool. The client initiates the request and you handle the binary stream within your standard app flow.

Your data stays private because this MCP server acts as a direct bridge. We use encrypted transport tokens to ensure only your authorized client interacts with your account.

Call `get_account_info` from your agent. It returns your current plan details and usage metrics so you can build logic around your remaining quota.

You can use `list_webhooks` to inspect your current configuration. This lets your AI client verify that your events are correctly registered.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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