How to Use the HowLongToBeat MCP in Vercel AI SDK

Q: How do I use the Vercel AI SDK to get HowLongToBeat data for 'Elden Ring'?

Pass the searchgametimes tool to the generateText function. Your agent will call the tool with the game name, and the AI SDK will stream the completion times directly into your UI components.

Q: Can I build a real-time search bar for game times with this?

Yes. You can trigger a streamText call on every keystroke, feeding the searchgametimes tool. The results will update live in your app, giving users instant feedback as they type.

Stream HowLongToBeat data directly into your UI with the Vercel AI SDK. No spinners, just results.

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Connect HowLongToBeat MCP to Vercel AI SDK

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

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Live Game Data in Your UI

The `search_game_times` tool lets your AI client fetch game completion stats. With the Vercel AI SDK, you don't wait for the full response. The data streams directly into your React or Svelte components as it arrives. This means your users see main story, completionist, and other playtime metrics appear in real time. It's perfect for building interactive game databases or recommendation tools where speed feels instant. This MCP server handles the lookup; you just handle the display.

Build Recommendation Filters

Let users filter your game catalog by how much time they have. Your agent can use `search_game_times` to find games under 20 hours, or epic RPGs over 100. The AI SDK makes it easy to pass these results to your frontend state. You're not just showing data, you're building a feature. Combine this with other filters like genre or price to give users a way to find exactly what they're looking for, fast. This MCP server makes adding that data point trivial.

Edge-Ready MCP Server

Run your AI logic at the edge, right alongside your frontend. This MCP server for HowLongToBeat is fully compatible with Vercel Edge Functions, so lookups are fast, no matter where your users are. Just connect your AI SDK client and your agent can start calling `search_game_times` with minimal latency. We manage the server, you focus on building a snappy UI.

Setup guide

Set up HowLongToBeat 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 HowLongToBeat 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 HowLongToBeat transactions",
});

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

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Common questions about HowLongToBeat MCP in Vercel AI SDK

Pass the `search_game_times` tool to the `generateText` function. Your agent will call the tool with the game name, and the AI SDK will stream the completion times directly into your UI components.

Yes. You can trigger a `streamText` call on every keystroke, feeding the `search_game_times` tool. The results will update live in your app, giving users instant feedback as they type.

Display the 'Main Story' time first, as that's what most people look for. Then, progressively show 'Main + Extra' and 'Completionist' times as they stream in. This gives users the most important info immediately.

No, it works with any framework the Vercel AI SDK supports. That includes React, Svelte, and Vue. The core benefit of streaming tool results is consistent across all of them.

Only the game titles you search for. The server receives a game name, looks up its completion time, and returns the hours. No personal data, user accounts, or gameplay history is ever accessed or stored.

Use it with your favorite AI tools

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

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