How to Use the Vast.ai (GPU Rental Cloud API) MCP in Vercel AI SDK

Q: How do I check GPU availability with Vast.ai (GPU Rental Cloud API) in Vercel AI SDK?

Just call searchoffers. Your agent formats the query as a JSON string, like {"gpuname":{"eq":"RTX 4090"}}. The results stream directly to your component for immediate UI display.

Q: Can Vercel AI SDK manage my existing GPU rentals?

Yep. Use listinstances to pull a live list of all rented resources. You'll see the data appear in your stream, letting you show users exactly what they have running.

Q: What’s the process for renting new GPUs with Vast.ai (GPU Rental Cloud API) using Vercel AI SDK?

Your agent calls rentinstance when needed. Because this tool supports streaming, you'll get confirmation and setup details appearing in your UI in real time—no waiting required.

Q: What tools does Vercel AI SDK support?

It supports searchoffers, listinstances, rentinstance, and deleteinstance. These all give you granular control over GPU resources right from your streaming UI.

Stream GPU data instantly into your UI using the Vercel AI SDK.

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Connect Vast.ai (GPU Rental Cloud API) MCP to Vercel AI SDK

Create your Vinkius account to connect Vast.ai (GPU Rental Cloud API) 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 Vast.ai (GPU Rental Cloud API) with Vercel AI SDK

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Search for available GPUs on Vast.ai

Need to know what's out there? Your agent uses `search_offers` to query the entire marketplace, giving you a clean list of specific GPU types and availability. This means your front-end can immediately show pricing options or required specs without waiting for a full data payload. The results feed directly into your UI stream. You'll see the offers appear in real time as the user asks about different hardware, making the whole experience feel snappy and live.

List currently rented instances

To check what's already running, call `list_instances`. This tool lets your client pull a snapshot of all active GPU rentals. It’s perfect for showing the user their current fleet size or verifying an existing resource status. The data appears in the UI stream as soon as it resolves, so you don't have to deal with loading spinners while listing resources. The speed is key here.

Rent a new GPU instance

When the user decides they need more power, your agent calls `rent_instance`. This action provisions the necessary GPU resource and provides confirmation details. You'll get the initial setup info streamed right into your component. This streaming capability means that even complex provisioning actions feel instantaneous to the end user, which is huge for a polished React or Next.js product.

Setup guide

Set up Vast.ai (GPU Rental Cloud API) 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 Vast.ai (GPU Rental Cloud API) 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 Vast.ai (GPU Rental Cloud API) 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 Vast.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 Vast.ai (GPU Rental Cloud API) MCP in Vercel AI SDK

Just call `search_offers`. Your agent formats the query as a JSON string, like {"gpu_name":{"eq":"RTX 4090"}}. The results stream directly to your component for immediate UI display.

Yep. Use `list_instances` to pull a live list of all rented resources. You'll see the data appear in your stream, letting you show users exactly what they have running.

Your agent calls `rent_instance` when needed. Because this tool supports streaming, you'll get confirmation and setup details appearing in your UI in real time—no waiting required.

The server touches instance metadata (GPU names, IDs). Since this is an Edge Function compatible tool, it's designed for low-latency reads and writes directly into your user interface.

It supports `search_offers`, `list_instances`, `rent_instance`, and `delete_instance`. These all give you granular control over GPU resources right from your streaming UI.

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