How to Use the HQBeds MCP in OpenAI Agents SDK

Build production-grade booking agents with OpenAI Agents SDK. Connect HQBeds to your pipeline for secure, automated reservation management.

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Connect HQBeds MCP to OpenAI Agents SDK

Create your Vinkius account to connect HQBeds to OpenAI Agents 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 HQBeds with OpenAI Agents SDK

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Safe reservation management for OpenAI Agents SDK

Your agent can handle bookings directly by calling `create_reservation`. The SDK automatically enforces guardrails on these calls to ensure every booking matches your strict business logic before it hits the HQBeds backend. You avoid manual errors by letting your agent pull specific guest records via `get_guest`. This keeps your reservation flow tight and prevents data leakage during agent handoffs.

Real-time occupancy tracking in OpenAI Agents SDK

Keep your agent informed by using `list_availability` with ISO 8601 dates. It gives your system an exact snapshot of open inventory, which the agent uses to answer guest queries without needing a human to check the dashboard. Since you're building a production system, you'll appreciate how `list_rooms` provides the raw data needed for your agent to suggest the right accommodations. It maps your internal inventory directly to the agent's decision-making process.

Automated status checks for OpenAI Agents SDK

Your agent can verify system connectivity instantly using `check_hqbeds_status`. It logs the health of the connection, ensuring your agent never attempts to process a booking while the service is unreachable. Use `list_reservations` to feed your agent a daily summary of incoming traffic. This allows your agent to proactively manage hostel operations and keep your team updated on the current load.

Setup guide

Set up HQBeds MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all HQBeds tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives HQBeds tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate HQBeds tools and returns structured results. Copy the full example on the right to get started.

agent.py

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

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="HQBeds Agent",
            instructions="You have access to HQBeds tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 HQBeds. 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 HQBeds MCP in OpenAI Agents SDK

You pass the server URL to the MCPServerStreamableHttp constructor. Once you add it to your Agent's mcp_servers list, your agent discovers the tools automatically.

Yes. The SDK validates every action against your defined constraints. You maintain full control over what the agent can actually execute.

Absolutely. Set cacheToolsList to True in your config to speed up agent initialization. It keeps your production system snappy.

It does. The server is designed to work with async context managers, matching the native flow of the agent framework perfectly.

The server only touches the specific guest and reservation records you request. Your agent receives only the data required to complete the current task.

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