Can I find out how long 'Elden Ring' takes to 100%?

Yes! Use the `search_game_times` tool with the query 'Elden Ring'. It will return the average hours for different playstyles, including the 'Completionist' run which is usually over 130 hours.

Where does the data come from?

The data is crowdsourced from thousands of gamers worldwide who submit their actual completion times to the HowLongToBeat community platform.

What is the difference between 'Main + Extra' and 'Completionist'?

'Main + Extra' includes the story plus some side content, while 'Completionist' represents finishing everything the game has to offer (100% trophies/achievements).

HowLongToBeat MCP Server for OpenAI Agents SDK 1 tools — connect in under 2 minutes

Name: HowLongToBeat
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 1 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect HowLongToBeat through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="HowLongToBeat Assistant",
            instructions=(
                "You help users interact with HowLongToBeat. "
                "You have access to 1 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from HowLongToBeat"
        )
        print(result.final_output)

asyncio.run(main())

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* 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 OpenAI Agents SDK auto-discovers all 1 tools from HowLongToBeat through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries HowLongToBeat, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

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 OpenAI Agents 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the HowLongToBeat MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 1 tools from HowLongToBeat

Why Use OpenAI Agents SDK with the HowLongToBeat MCP Server

OpenAI Agents SDK provides unique advantages when paired with HowLongToBeat through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

HowLongToBeat + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the HowLongToBeat MCP Server delivers measurable value.

Automated workflows: build agents that query HowLongToBeat, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries HowLongToBeat, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through HowLongToBeat tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query HowLongToBeat to resolve tickets, look up records, and update statuses without human intervention

HowLongToBeat MCP Tools for OpenAI Agents SDK (1)

These 1 tools become available when you connect HowLongToBeat to OpenAI Agents SDK via MCP:

search_game_times

Search for game completion times

Example Prompts for HowLongToBeat in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents 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 OpenAI Agents SDK

Common issues when connecting HowLongToBeat to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

HowLongToBeat + OpenAI Agents SDK FAQ

Common questions about integrating HowLongToBeat MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.