How to Use the Condeco (Eptura Engage) MCP in OpenAI Agents SDK

Q: How do I handle booking cancellations in Condeco (Eptura Engage) with OpenAI Agents SDK?

Your agent runs cancelroombooking or canceldeskbooking when a user requests a cancellation. OpenAI's native guardrails validate the cancellation request against O365 sync boundaries before the tool executes.

Book Condeco rooms and desks directly inside your production OpenAI Agents SDK workflows.

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Connect Condeco (Eptura Engage) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Condeco (Eptura Engage) 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 Condeco (Eptura Engage) with OpenAI Agents SDK

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Run secure office bookings inside your OpenAI Agents SDK

This Condeco (Eptura Engage) MCP Server provides the `list_rooms` and `get_room_availability` tools directly to your OpenAI Agents SDK. Your agents call these tools to parse enterprise real estate limits and check open slots before committing to any meeting space. Built-in tracing on the OpenAI dashboard records every lookup. Because you set cacheToolsList to true, your agents discover these workspace endpoints instantly without lagging your production runtime.

Automated desk reservation lifecycle in OpenAI Agents SDK

This Condeco (Eptura Engage) MCP Server exposes `book_desk` and `cancel_desk_booking` to handle hot desking bounds directly from your Python runtime. Your OpenAI Agents SDK coordinates desk claims and cancellations based on real-time developer schedules. Specialized agents hand off tasks to each other when reservations change. If a developer cancels their shift, one agent triggers `cancel_desk_booking` while another reallocates the slot, keeping your office occupancy logs accurate.

Verify physical presence using OpenAI Agents SDK

This Condeco (Eptura Engage) MCP Server connects `check_in_to_location` directly to your OpenAI Agents SDK for automated badge-in verification. Your agent processes location check-ins by executing local access controls when employees arrive at the office. Running this via MCPServerStreamableHttp ensures low-latency execution. Physical arrivals are logged securely, matching occupancy data with real-time room bookings without manual overhead.

Setup guide

Set up Condeco (Eptura Engage) 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 Condeco (Eptura Engage) tools at runtime.
3

Create your Agent

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

Run the agent

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

You pass the MCPServerStreamableHttp instance directly into the Agent constructor. The SDK automatically registers tools like `list_desks` and `book_desk` with no manual JSON schema writing required.

Yes, you control this by configuring the server URL with specific permissions. Your OpenAI Agents SDK only executes `book_room` on the meeting spaces allowed by your Vinkius gateway credentials.

Your agent runs `cancel_room_booking` or `cancel_desk_booking` when a user requests a cancellation. OpenAI's native guardrails validate the cancellation request against O365 sync boundaries before the tool executes.

No, Vinkius hosts the server in a secure sandbox. Your OpenAI Agents SDK connects directly to the managed HTTP endpoint, eliminating the need to manage local dependencies or runtime environments.

Vinkius processes all check-in data and room schedules within ephemeral V8 isolates. Your OpenAI Agents SDK never exposes raw employee location histories or physical security credentials to third-party servers.

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