How to Use the ZEGO / 即构科技 MCP in OpenAI Agents SDK
Manage real-time comms and user actions using your OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect ZEGO / 即构科技 MCP to OpenAI Agents SDK
Create your Vinkius account to connect ZEGO / 即构科技 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.
Monitor Room Activity
Use `list_rooms` to get a rundown of every active room on the platform. You can then call `get_room_users` to see exactly who is in that space. Need more detail? Call `get_room_streams` to list all active media streams within a specific room, and use `get_online_count` for the total user tally across the service.
Control User Presence
The agent executes direct moderation actions. You can kick users immediately using `kick_room_user`. It also lets you stop a live feed by calling `stop_media_stream`. Keep tabs on who's online with `check_user_status`, which verifies the current state of multiple connected accounts. This is crucial for building stable, production-ready agent logic.
Audit Service Usage
To build a full picture of service health, run `get_usage_stats` to gather detailed metrics on platform usage. You can also get the list of rooms using `list_rooms` and check which users are present via `get_room_users`. This MCP Server helps you audit everything. It provides necessary data points like room listings, user counts, and total system activity.
Set up ZEGO / 即构科技 MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all ZEGO / 即构科技 tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives ZEGO / 即构科技 tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate ZEGO / 即构科技 tools and returns structured results. Copy the full example on the right to get started.
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="ZEGO / 即构科技 Agent",
instructions="You have access to ZEGO / 即构科技 tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ZEGO / 即构科技. 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.
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 ZEGO / 即构科技 MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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