How to Use the Cerebras Inference MCP in Vercel AI SDK

Q: How do I stream Cerebras Inference chat responses with the Vercel AI SDK?

Pass the createchatcompletion tool to the streamText function from the AI SDK. It handles the streaming connection automatically. You'll get back an async iterator that yields tokens as the Cerebras model generates them.

Q: Can I manage batch jobs on Cerebras Inference using the Vercel AI SDK?

Yes. The SDK exposes tools like createbatch, getbatch, and listbatches. You can call these from your serverless functions to start and monitor jobs, then use getfilecontent to download the results.

Q: Is it possible to list available models from Cerebras Inference in a Vercel AI SDK app?

Absolutely. Use the listmodels tool to get a JSON list of available inference models. You can then display this in your UI, letting users choose which model to run their prompts against.

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Connect Cerebras Inference MCP to Vercel AI SDK

Create your Vinkius account to connect Cerebras Inference 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 Cerebras Inference with Vercel AI SDK

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Live Chat Completions in Your UI

Use the `create_chat_completion` tool to feed conversational AI directly into your UI components. The Vercel AI SDK streams the response token-by-token, so your users see the answer typing out in real time. It feels fast because it is. You can also list available models with `list_models` and `list_public_models` to build a model selector right in your app. Let users pick the right Cerebras model for their task without ever leaving your product.

Manage Batch Jobs from the Frontend

The `create_batch` tool lets your users kick off long-running inference jobs on large datasets. They can upload a JSONL file using `upload_file` and start processing without blocking the main thread. While the job runs, you can build a status dashboard. Use `get_batch` and `list_batches` to poll for updates and display progress. When it's done, `get_file_content` pulls the results right back into the browser.

Your Vercel AI SDK MCP Server

This isn't just about text generation. You get full control over your files on the Cerebras platform. The `list_files` tool gives you a directory, and `delete_file` cleans up old data. Need to check the server's health? The `get_metrics` tool exposes Prometheus-formatted metrics. This MCP server gives you the building blocks to see what's going on under the hood.

Setup guide

Set up Cerebras Inference 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 Cerebras Inference 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 Cerebras Inference 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 Cerebras Inference. 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 Cerebras Inference MCP in Vercel AI SDK

Pass the `create_chat_completion` tool to the `streamText` function from the AI SDK. It handles the streaming connection automatically. You'll get back an async iterator that yields tokens as the Cerebras model generates them.

Yes. The SDK exposes tools like `create_batch`, `get_batch`, and `list_batches`. You can call these from your serverless functions to start and monitor jobs, then use `get_file_content` to download the results.

Absolutely. Use the `list_models` tool to get a JSON list of available inference models. You can then display this in your UI, letting users choose which model to run their prompts against.

Vinkius gives you a single endpoint token. You pass this token when you initialize the MCP client in your backend code. The SDK's `authProvider` also supports more complex OAuth flows if you need them.

Your uploaded JSONL files are processed inside a V8 Isolate sandbox on Vinkius. The connection is ephemeral, and the `delete_file` tool gives you direct control to remove your data permanently from the server after a job is complete.

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