How to Use the Common Room MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK handle Common Room activity logs?

Yes. Your agent calls listactivitytypes to understand what actions are available. It then processes these events based on your specific logic.

Directly manage Common Room community data inside your OpenAI Agents SDK projects with zero configuration overhead.

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Connect Common Room MCP to OpenAI Agents SDK

Create your Vinkius account to connect Common Room 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 Common Room with OpenAI Agents SDK

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Manage segments via OpenAI Agents SDK

Your agent uses `add_contact_to_segment` and `list_segments` to organize community members on the fly. It bypasses manual dashboard navigation entirely. This MCP Server feeds real-time member counts directly into your agent logic. You get accurate data for every automated workflow.

Search contacts in OpenAI Agents SDK

Call `search_contacts` or `get_contact_by_email` to pull member profiles into your agent context. It identifies who you are talking to before you send a single message. Your production agent validates these records against your safety constraints. It prevents unauthorized contact modifications through strict action checks.

Track organization data in OpenAI Agents SDK

Use `get_organization_details` to pull firmographic data into your agent memory. You can now qualify leads based on real-time Common Room intelligence. `search_organizations` lets your agent find the right account in seconds. It keeps your CRM data fresh without manual imports.

Setup guide

Set up Common Room 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 Common Room tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK and define an MCPServerStreamableHttp instance with your Vinkius endpoint. Your agent automatically maps the tools once you pass the server to the constructor.

Yes. Your agent calls `list_activity_types` to understand what actions are available. It then processes these events based on your specific logic.

It does. Set cacheToolsList to True to speed up your agent performance. This avoids repeated server calls for static tool definitions.

Vinkius handles all authentication via a single endpoint token. Your agent only communicates over encrypted channels to keep your community data private.

The server accesses email addresses, contact tags, and organization names. We isolate these requests in a sandbox to ensure your PII stays protected.

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