How to Use the CoreWeave (AI GPU Cloud) MCP in Vercel AI SDK

Q: Does CoreWeave (AI GPU Cloud) support Vercel AI SDK log streaming?

It does. You use querylogs to pull Loki data into your stream, allowing your frontend to display live debug info directly from your GPU nodes.

Provision GPU clusters and manage inference gateways directly in Vercel AI SDK to keep your frontend state in sync with infrastructure.

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Connect CoreWeave (AI GPU Cloud) MCP to Vercel AI SDK

Create your Vinkius account to connect CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) with Vercel AI SDK

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Real-time GPU cluster management in Vercel AI SDK

You can spin up new infrastructure without leaving your TypeScript environment. Just call `create_cluster` or `create_deployment` to trigger backend provisioning while your UI updates instantly. This MCP Server handles the handshake so your React components render infrastructure status as it happens. You avoid the lag of manual console toggling by piping `list_clusters` results straight into your state.

Stream inference metrics to Vercel AI SDK

Pipe live infrastructure health data directly into your dashboard components. Use `query_metrics` to grab Prometheus data and render it in real-time as your AI agent monitors the deployment. Your users see the performance of their GPU nodes immediately. Because the tools stream responses, you don't need to build custom polling logic to track your `create_gateway` progress.

Ephemeral VPC control for Vercel AI SDK

Isolate your workloads by creating and tearing down virtual networks on the fly. You run `create_vpc` and `delete_vpc` as part of your deployment lifecycle, keeping your environment clean. This approach ensures your AI client manages networking as code. You aren't just reading configs; you are actively defining your cloud topology from your application logic.

Setup guide

Set up CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) transactions",
});

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

Get your connection token →

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Common questions about CoreWeave (AI GPU Cloud) MCP in Vercel AI SDK

Install the MCP packages and point your client to the Vinkius endpoint. You define your credentials once, and your agent gains access to the full suite of deployment tools.

Yes, you can script auto-scaling logic using the capacity claim tools. Your agent checks available resources and triggers new claims when demand spikes.

It does. You use `query_logs` to pull Loki data into your stream, allowing your frontend to display live debug info directly from your GPU nodes.

Vinkius handles the underlying auth so you don't leak secrets in your repository. Your keys stay on our isolated runtime, not in your code.

The server only interacts with your cluster configurations, VPC definitions, and inference metrics. It never reads your user-facing application database or personal logs.

Use it with your favorite AI tools

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