How to Use the Airmeet MCP in OpenAI Agents SDK

Q: How do I connect the Airmeet MCP Server to OpenAI Agents SDK?

Install openai-agents via pip. Initialize MCPServerStreamableHttp with your Vinkius endpoint URL. Pass the server object into the mcpservers list when building your Agent instance.

Deploy production event workflows using the Airmeet MCP Server and OpenAI Agents SDK.

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Connect Airmeet MCP to OpenAI Agents SDK

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

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Perplexity

Automate Airmeet events in OpenAI Agents SDK

Hooking up your agent to run webinars means handling state changes. You pass the endpoint token into your initialization and the agent discovers the tools. It fires `create_event` to spin up the base container, then loops through `create_session` to build out the daily schedule. Production systems need strict guardrails. If an agent tries to push an invalid time block, validation catches it before execution. You track the whole setup process via the dashboard, ensuring the script does not spam `update_event_status` by accident.

Register users and track attendance

Getting people into the room is half the job. Your agent calls `add_attendee` to push new signups directly into the platform. Once the broadcast finishes, it pulls `get_event_attendance` to calculate drop-off rates and engagement metrics. Handoffs work perfectly here. One specialized agent handles the registration queue. Another takes over post-event, running `list_participants` to match attendees against your CRM records. Everything stays traced and logged in the OpenAI dashboard.

Process recordings and audience Q&A

You need the raw video files to cut marketing clips. The agent hits `get_session_recordings` to grab the secure download links. It hands those URLs off to a transcription pipeline without you clicking through web interfaces. Audience interaction data comes out just as cleanly. Running `list_questions` and `list_poll_responses` pulls the raw text from the chat. Your system can then categorize what the crowd asked and feed it straight into your next content strategy.

Setup guide

Set up Airmeet 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 Airmeet tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Airmeet 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="Airmeet Agent",
            instructions="You have access to Airmeet 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 Airmeet MCP in OpenAI Agents SDK

Install `openai-agents` via pip. Initialize `MCPServerStreamableHttp` with your Vinkius endpoint URL. Pass the server object into the `mcp_servers` list when building your Agent instance.

The integration handles this instantly. Once connected, the SDK auto-discovers all available endpoints like `create_session` and `list_events`. Turn on `cacheToolsList=True` to speed up initialization.

Built-in guardrails validate the inputs before the agent makes a network call. If a parameter for `add_attendee` is missing, the system catches the fault locally. You see the exact failure point in your tracing dashboard.

You run the whole setup inside an async context manager. This lets your agent fire `update_event_status` while concurrently handling other network requests. Production deployments will not block the main thread.

Your Vinkius sandbox operates on a zero-trust model. The server processes names, emails, and poll responses from `list_participants` ephemerally. No virtual event records persist in the isolation layer after the session ends.

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