HowLongToBeat MCP Server for Vercel AI SDK 1 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect HowLongToBeat through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using HowLongToBeat, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About HowLongToBeat MCP Server
Equip your AI agent with the ultimate gaming library intelligence via the HowLongToBeat MCP server. This integration provides instant access to the world's most trusted source for game completion times. Your agent can search for any video game and retrieve precise timing data for the 'Main Story', 'Main + Extra', and 'Completionist' runs. Whether you're planning your backlog, deciding on your next purchase, or auditing your play style, your agent acts as a dedicated gaming advisor through natural conversation.
The Vercel AI SDK gives every HowLongToBeat tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 1 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Game Time Search — Find how long it takes to beat any video game.
- Playstyle Comparison — Compare durations for different completion levels (story vs. 100%).
- Release Intelligence — Retrieve world release dates and exact game titles for thousands of entries.
- Backlog Auditing — Summarize expected playtimes for entire lists of games.
The HowLongToBeat MCP Server exposes 1 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect HowLongToBeat to Vercel AI SDK via MCP
Follow these steps to integrate the HowLongToBeat MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 1 tools from HowLongToBeat and passes them to the LLM
Why Use Vercel AI SDK with the HowLongToBeat MCP Server
Vercel AI SDK provides unique advantages when paired with HowLongToBeat through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same HowLongToBeat integration everywhere
Built-in streaming UI primitives let you display HowLongToBeat tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
HowLongToBeat + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the HowLongToBeat MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query HowLongToBeat in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate HowLongToBeat tools and return structured JSON responses to any frontend
Chatbots with tool use: embed HowLongToBeat capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with HowLongToBeat through natural language queries
HowLongToBeat MCP Tools for Vercel AI SDK (1)
These 1 tools become available when you connect HowLongToBeat to Vercel AI SDK via MCP:
search_game_times
Search for game completion times
Example Prompts for HowLongToBeat in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with HowLongToBeat immediately.
"How long does it take to beat the main story of The Witcher 3?"
"Is 'Hades' a short game for a completionist?"
"Compare the completion times for 'Skyrim' and 'Starfield'."
Troubleshooting HowLongToBeat MCP Server with Vercel AI SDK
Common issues when connecting HowLongToBeat to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpHowLongToBeat + Vercel AI SDK FAQ
Common questions about integrating HowLongToBeat MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect HowLongToBeat with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect HowLongToBeat to Vercel AI SDK
Get your token, paste the configuration, and start using 1 tools in under 2 minutes. No API key management needed.