How to Use the Arbox MCP in OpenAI Agents SDK
Manage your gym's daily operations directly inside your OpenAI Agents SDK production environment.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Arbox MCP to OpenAI Agents SDK
Create your Vinkius account to connect Arbox 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.
Automate class bookings in OpenAI Agents SDK
Your agent handles member schedules without manual intervention. It calls `book_class` to secure spots and uses `list_classes` to verify availability. Everything happens within your Python execution loop. You'll see the exact class times and member status updates in your OpenAI dashboard traces.
Track member lifecycle via OpenAI Agents SDK
Stop digging through spreadsheets to find contact info. Use `get_client` or `list_clients` to pull member profiles directly into your agent's context window. Updating records stays simple with `update_client`. Your agent applies these changes instantly, ensuring your local data matches the gym's database.
Manage gym tasks with OpenAI Agents SDK
Keep your staff organized by creating actionable items. The agent triggers `create_task` based on member queries or session outcomes. Use `list_tasks` to check what's pending. It keeps your workflow moving without leaving your Python code.
Set up Arbox MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Arbox tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Arbox tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Arbox tools and returns structured results. Copy the full example on the right to get started.
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="Arbox Agent",
instructions="You have access to Arbox tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main())Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Arbox. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Arbox MCP in OpenAI Agents SDK
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