How to Use the Apify MCP in Vercel AI SDK

Q: How do I handle errors during Apify runs in Vercel AI SDK?

Use getrun to poll for status updates. If a job fails, you can catch the error in your code and trigger a cleanup.

Run Apify scrapers directly from your Vercel AI SDK projects to stream web data into your React or Next.js interfaces.

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Connect Apify MCP to Vercel AI SDK

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

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Trigger Apify actors in Vercel AI SDK

Start your scraping jobs by calling `run_actor` or `run_actor_sync` directly from your server-side functions. You get the run ID immediately, letting your UI handle state updates while the job processes in the background. Since this MCP Server integrates with the SDK, you can pipe the output into your streams. Your users see the data populate the page the moment it arrives, avoiding those endless loading spinners.

Fetch Apify datasets into Vercel AI SDK

Pull structured JSON data into your frontend using `get_dataset_items`. You can set pagination limits to handle large result sets without choking your edge functions. This keeps your data flow clean. Just pass the dataset ID from your run object, and the server returns the records ready for your components to render.

Monitor Apify usage in Vercel AI SDK

Keep an eye on your compute consumption by invoking `get_account_limits`. This prevents your production apps from hitting unexpected billing caps during high-traffic scraping tasks. It helps you stay proactive. You can write logic to pause or throttle requests before you burn through your monthly units.

Setup guide

Set up Apify 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 Apify 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 Apify 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 Apify. 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 Apify MCP in Vercel AI SDK

Install the MCP client packages and point them to the Vinkius endpoint. You initialize the client and pass the tools into your generateText calls to start scraping.

Yes, the tools work with standard streaming responses. Data extracted via the MCP Server renders in your UI as it arrives.

No, but you can check your status using the toolset. This ensures your app stays within the limits set by your account.

Use `get_run` to poll for status updates. If a job fails, you can catch the error in your code and trigger a cleanup.

Vinkius uses isolated sandboxes for every session. Your account keys and scraped JSON content never touch public logs.

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