How to Use the Hubilo MCP in OpenAI Agents SDK

Q: How does this MCP Server handle large attendee lists in OpenAI Agents SDK?

The server handles pagination for tools like listattendees behind the scenes. Your agent receives structured JSON chunks, which prevents context window overflows and keeps your token usage under control.

Q: Is there latency overhead when using Hubilo with OpenAI Agents SDK?

Setting cacheToolsList=True in your server configuration reduces startup latency. Since Vinkius runs on V8 sandboxes, MCP tool discovery takes milliseconds, leaving API rate limits as your only real bottleneck.

Build production-grade virtual event agents using OpenAI Agents SDK to query registration lists and run booth metrics without manual code.

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Connect Hubilo MCP to OpenAI Agents SDK

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

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Validate event actions with OpenAI Agents SDK guardrails

Production agents need boundaries. When your agent queries attendee databases using `list_attendees` or checks financials with `list_orders`, you cannot risk runaway loops or unauthorized lookups. This setup maps Hubilo tools directly into your system, letting you apply hard guardrails before any API request fires. You get clean execution logs on the OpenAI dashboard. If an agent tries to pull ticket details via `list_tickets` without the right context, the guardrail catches it immediately. No unexpected API bills or security leaks.

Coordinate specialized agents for booth and speaker data

Don't force a single agent to handle everything. Designate one agent for exhibitor data and another for logistics. One agent pulls booth performance with `get_booth_analytics` and `list_booth_categories`, while another handles agendas. The SDK manages the handoffs. When a user asks about speaker schedules, the booth agent passes the conversation to the speaker agent, which calls `list_speakers` and `list_sessions`. It keeps your logic modular and easy to debug.

Auto-discover Hubilo tools for rapid deployment

Skip writing boilerplate wrapper code. This MCP Server lets your OpenAI Agents SDK automatically scan and register all ten Hubilo endpoints. Your agent instantly understands how to grab event configurations via `get_event_details` and organizer details using `get_organizer_profile`. It is a zero-configuration integration. Just spin up the streamable HTTP server and pass it to your agent constructor. The agent immediately knows what arguments to send to `list_events` without you writing a single line of schema definition.

Setup guide

Set up Hubilo 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 Hubilo tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Hubilo 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="Hubilo Agent",
            instructions="You have access to Hubilo tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Hubilo MCP in OpenAI Agents SDK

You install the library and initialize the streamable HTTP transport pointing to your Vinkius endpoint. Pass this server instance inside the `mcp_servers` list when creating your Agent. The SDK auto-discovers all tools from this MCP integration instantly.

Yes, you can control tool access using the SDK's native guardrails or by configuring the endpoint on Vinkius. If you want to block agents from viewing financial data, you can intercept calls to `list_orders` or `list_tickets` before they reach the server.

The server handles pagination for tools like `list_attendees` behind the scenes. Your agent receives structured JSON chunks, which prevents context window overflows and keeps your token usage under control.

Setting `cacheToolsList=True` in your server configuration reduces startup latency. Since Vinkius runs on V8 sandboxes, MCP tool discovery takes milliseconds, leaving API rate limits as your only real bottleneck.

Your attendee profiles, ticket purchases, and booth metrics remain secure because Vinkius routes requests through an ephemeral, zero-trust sandbox. The SDK never exposes your master Hubilo API keys to the LLM; it only transmits the specific data returned by tools like `list_attendees` or `get_booth_analytics`.

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