How to Use the Momence MCP in OpenAI Agents SDK

Q: How do I connect my Momence studio to the OpenAI Agents SDK?

Install openai-agents via pip and configure the streamable HTTP server using your Vinkius endpoint token. Pass the server instance directly into your Agent constructor's mcpservers list to auto-discover all studio tools.

Q: How does the OpenAI Agents SDK handle Momence rate limits?

Set cacheToolsList=True in your SDK configuration to prevent redundant schema fetches. This minimizes external API calls when querying listsessions or listteachers repeatedly.

Build production-grade OpenAI agents with this MCP Server to manage Momence studio bookings, schedules, and memberships.

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Connect Momence MCP to OpenAI Agents SDK

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

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Guarded Momence booking workflows with OpenAI Agents SDK

This MCP Server hooks directly into your Python agent, letting it pull up live class schedules using `list_sessions` and check who is signed up via `list_bookings`. Because you are running the OpenAI Agents SDK, your agent can safely coordinate check-ins and spot booking conflicts before they mess up your morning rush. The SDK handles tool discovery automatically. When a member calls in to change their spot, the agent uses `get_member` to verify their active plan with `list_memberships` and processes the update under strict execution guardrails that you define in your Python code.

Intelligent teacher scheduling and studio coverage

Managing last-minute shift changes is a nightmare. This integration lets your OpenAI Agents SDK agent scan available staff using `list_teachers` and swap instructors for specific classes found via `get_session`. You can set up specialized agents—one for member relations, another for staff scheduling—and let the SDK handle the handoffs. The scheduling agent looks up the right class format with `list_session_types` while the member agent handles notifications, all tracked in your OpenAI dashboard.

Inventory tracking and retail sales at the front desk

Keep your retail desk running without manual data entry. Your agent queries available inventory using `list_products` and cross-references it with specific studio spots found through `list_locations`. The SDK caches these tools using the `cacheToolsList=True` parameter to keep response times under a second. Your agent can instantly tell a client if their favorite yoga mat is in stock at their local branch when they check in.

Setup guide

Set up Momence 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 Momence tools at runtime.
3

Create your Agent

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

Run the agent

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

Install `openai-agents` via pip and configure the streamable HTTP server using your Vinkius endpoint token. Pass the server instance directly into your Agent constructor's `mcp_servers` list to auto-discover all studio tools.

Yes. You can write custom guardrails in Python that intercept tool calls like `list_bookings` before execution, ensuring the agent verifies class capacity limits before confirming a spot.

Set `cacheToolsList=True` in your SDK configuration to prevent redundant schema fetches. This minimizes external API calls when querying `list_sessions` or `list_teachers` repeatedly.

Yes. The SDK supports native agent handoffs, meaning you can have one agent handle profile updates with `get_member` and hand off to a billing agent when looking up `list_memberships`.

Vinkius runs this MCP Server inside an ephemeral, zero-trust V8 Isolate sandbox. Your sensitive member profiles, class lists, and booking records are never stored, and all requests require a single secure endpoint token.

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