How to Use the Luma MCP in OpenAI Agents SDK

Manage event registrations and guest lists directly from your Python agent using the OpenAI Agents SDK.

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Connect Luma MCP to OpenAI Agents SDK

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

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Automate guest list management

Your agent handles attendee lists without manual data entry. Use `add_guests_to_event` to push your contact lists into specific sessions directly from your code. This keeps your event records current. Your agent checks `list_event_guests` to verify who is attending before it takes further action.

Programmatic event creation

Stop jumping between browser tabs to set up your calendar. Your agent uses `create_event` to spin up new registration pages based on your specific event parameters. Everything stays inside your Python environment. You track your progress by calling `list_events` to confirm your new pages are live.

Monitor organization-wide activity

Your agent pulls real-time data from your entire team using `list_organization_events`. It processes this data to surface high-priority events that need attention. This MCP Server feeds clean, structured data into your agent logic. It eliminates the need for manual reporting across your different departments.

Setup guide

Set up Luma 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 Luma tools at runtime.
3

Create your Agent

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

Run the agent

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

Use the MCPServerStreamableHttp class to point your agent at your Vinkius endpoint. Pass this as an mcp_servers list to your Agent constructor to enable automatic tool discovery.

Yes. Your agent iterates through guest data using the list tools provided by the MCP Server. It processes these records in memory to manage your invitations.

Your agent only accesses data you explicitly authorize. We use ephemeral, zero-trust connections to ensure your event details remain isolated during every request.

The MCP standard keeps your agent code stable. Your agent interacts with the tools provided by the server, which abstracts away underlying API shifts.

The SDK provides full tracing for every call. If an event creation fails, you see exactly which tool parameter caused the issue in your logs.

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