How to Use the Huddle01 (Web3 Video API) MCP in OpenAI Agents SDK

Q: How do I connect the Huddle01 (Web3 Video API) MCP Server to the OpenAI Agents SDK?

Install the package via pip install openai-agents. Initialize the connection using MCPServerStreamableHttp with your endpoint URL, and pass it to your agent's mcpservers array.

Q: Can the Huddle01 (Web3 Video API) track active callers with the OpenAI Agents SDK?

Yes. The server exposes getlivesessiondetails to monitor active rooms. Your agent can validate the output against its safety constraints before taking action.

Q: How does the OpenAI Agents SDK handle Huddle01 (Web3 Video API) rate limits?

You can set cacheToolsList=True during initialization to reduce discovery overhead. The agent checks your usage via getmetrics and triggers a handoff if limits approach the threshold.

Provision Web3 video rooms and track live sessions safely using the OpenAI Agents SDK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Huddle01 (Web3 Video API) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Huddle01 (Web3 Video API) 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.

GDPR Free for Subscribers

Setup Huddle01 (Web3 Video API) with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Provision locked rooms via OpenAI Agents SDK

The `create_room` MCP tool lets your agent provision new Huddle01 meeting spaces on demand, requiring a strict locked status parameter. Your production system can spin up these environments automatically while logging the exact API calls in the OpenAI dashboard. The agent executes the creation and hands off the room ID to a specialized notification agent. You get full tracing on the backend. This ensures no rogue scripts drain your API limits.

Monitor live session metrics

Using the `get_live_sessions` and `get_live_session_participants` tools, your agent tracks exactly who joins active rooms in real time. Built-in guardrails in the OpenAI Agents SDK validate these requests before execution so your agent never spams the Huddle01 API. Once a meeting ends, the agent pulls historical attendance via `get_participant_list`. You can set up safety constraints that prevent the agent from exposing participant data outside of specific, authorized channels.

Fetch Web3 video recordings

The `get_recordings` tool retrieves media files for completed calls, filtering specifically by session ID. Your agent can pull these assets directly into your processing pipeline as soon as a meeting concludes. By caching the MCP tool list with `cacheToolsList=True`, your agent skips the discovery phase and jumps straight to pulling the recording data. You verify the exact retrieval sequence through OpenAI's tracing interface.

Setup guide

Set up Huddle01 (Web3 Video API) 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 Huddle01 (Web3 Video API) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Huddle01 (Web3 Video API) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Huddle01 (Web3 Video API) 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="Huddle01 (Web3 Video API) Agent",
            instructions="You have access to Huddle01 (Web3 Video API) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Huddle01. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Huddle01 (Web3 Video API) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Huddle01 (Web3 Video API) MCP in OpenAI Agents SDK

Install the package via `pip install openai-agents`. Initialize the connection using `MCPServerStreamableHttp` with your endpoint URL, and pass it to your agent's `mcp_servers` array.

Yes. The server exposes `get_live_session_details` to monitor active rooms. Your agent can validate the output against its safety constraints before taking action.

You can set `cacheToolsList=True` during initialization to reduce discovery overhead. The agent checks your usage via `get_metrics` and triggers a handoff if limits approach the threshold.

You must explicitly define whether a room is locked when calling `create_room`. The agent will fail the action if this parameter is missing, thanks to its built-in guardrails.

The server accesses room IDs, participant lists, and recording file locations. The OpenAI Agents SDK logs these data points in your tracing dashboard, so you retain complete visibility over what the agent reads and transmits.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript