How to Use the Cobot MCP in OpenAI Agents SDK

Run your coworking space autonomously by connecting Cobot directly to your OpenAI Agents SDK pipeline.

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Connect Cobot MCP to OpenAI Agents SDK

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

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Auto-discover Cobot tools in OpenAI Agents SDK

This MCP Server exposes `get_cobot_space_info` and `list_space_resources` to let your agents inspect your space. Your production pipeline can query real-time room availability instantly. You get clean execution logs in your OpenAI dashboard without writing glue code.

Safe booking execution with strict guardrails

The `create_new_booking` tool lets your agent write reservations directly to your calendar. This MCP setup protects your operations from rogue agent actions. You get the speed of automation while keeping absolute control over your physical space.

Smart billing and membership audits

Using `list_cobot_memberships` and `list_cobot_invoices`, your agent can audit your billing records via MCP. The system coordinates these tasks behind the scenes. It uses `list_membership_plans` to find unpaid accounts and flags them for follow-up without human intervention.

Setup guide

Set up Cobot 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 Cobot tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the package using pip install openai-agents. Then, initialize the streamable HTTP server and pass it inside the mcp_servers list of your Agent constructor.

Yes, you can restrict tool access at the agent level or configure your proxy settings. This prevents your agent from running sensitive operations like booking creation if it only needs read-only access.

The SDK relies on standard HTTP error handling and backoff strategies. If Cobot returns a rate limit error, the agent pauses and retries based on your configuration.

No, you do not. The MCP Server handles schema registration automatically, meaning your agent instantly understands how to call `list_membership_plans` without manual JSON schema writing.

Your membership details and invoice data are protected inside an isolated V8 sandbox. Every request goes through a single secure endpoint token, ensuring your tenant database remains locked down.

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