How to Use the ClubPlanner MCP in OpenAI Agents SDK

Q: How do I connect ClubPlanner to OpenAI Agents SDK?

Install the package with pip install openai-agents and define your MCP Server using MCPServerStreamableHttp. Pass this instance into your OpenAI Agent constructor's mcpservers list to auto-discover the ClubPlanner gym tools.

Run safe, production-grade gym operations with OpenAI Agents SDK and ClubPlanner.

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Connect ClubPlanner MCP to OpenAI Agents SDK

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

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Guarded member onboarding with OpenAI Agents SDK

This MCP Server exposes ClubPlanner tools to let your OpenAI agents safely register new gym-goers without manual data entry. By exposing `create_prospect` and `create_member` directly to your OpenAI agent constructors, you build self-service gym signup flows that run within your custom OpenAI guardrails. The OpenAI agent handles the conversation, while your defined validation rules stop invalid gym entries before they hit your ClubPlanner database. When a local lead reaches out, your OpenAI agent instantly runs `list_products` to pitch the right ClubPlanner membership tier. It then uses `create_appointment` to schedule their first gym tour, logging everything in ClubPlanner with full tracing visible on your OpenAI developer dashboard.

Smart staff handoffs for front-desk tasks

This MCP Server lets your OpenAI agents monitor gym attendance and triage front-desk issues dynamically using ClubPlanner data. If a gym member checks in using `create_checkin` and has an expired pass, the OpenAI agent detects the block via `list_contracts` and hands the conversation off to a specialized billing agent. This multi-agent OpenAI setup ensures that complex ClubPlanner billing issues route to the right LLM configuration. Your primary OpenAI agent keeps its focus on booking gym classes, while the billing specialist pulls `get_member` to resolve the ClubPlanner account hold without mixing up system prompts.

High-performance schedule lookups

This MCP Server speeds up gym scheduling by caching your ClubPlanner tool definitions for your OpenAI agent. Setting `cacheToolsList=True` ensures your python system doesn't waste precious milliseconds fetching ClubPlanner schemas on every OpenAI user query. Your OpenAI agents quickly scan `list_appointments` and `list_staff` to answer ClubPlanner scheduling questions in real-time. Gym members get instant replies about trainer availability, and your OpenAI backend avoids redundant API roundtrips to ClubPlanner.

Setup guide

Set up ClubPlanner 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 ClubPlanner tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate ClubPlanner 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="ClubPlanner Agent",
            instructions="You have access to ClubPlanner tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ClubPlanner. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about ClubPlanner MCP in OpenAI Agents SDK

Install the package with `pip install openai-agents` and define your MCP Server using `MCPServerStreamableHttp`. Pass this instance into your OpenAI Agent constructor's `mcp_servers` list to auto-discover the ClubPlanner gym tools.

Yes, you control ClubPlanner tool access at the OpenAI agent level. Define specialized OpenAI agents for front-desk tasks using `create_checkin` and separate sales agents that only have access to ClubPlanner's `create_prospect`.

The OpenAI Agents SDK relies on your host configuration to manage API traffic to ClubPlanner. Because Vinkius runs your server in an isolated zero-trust sandbox, your OpenAI agents get stable execution when running heavy lookups like `list_members`.

Yes, use an async context manager in Python to boot the OpenAI Agents SDK streamable HTTP client, allowing your agent to run ClubPlanner's `list_contracts` and `list_checkins` concurrently. This keeps your OpenAI event loop fully responsive while processing gym reports.

Vinkius handles ClubPlanner connection details inside an isolated zero-trust MCP sandbox. Your OpenAI agent only receives raw JSON payloads from tools like `get_member` and `list_prospects` over secure, ephemeral channels, meaning physical member check-ins, staff rosters, and prospect details are never cached or exposed.

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