How to Use the IP Parking MCP in OpenAI Agents SDK
Run production-grade OpenAI Agents SDK workflows that directly control physical gates and update rates via the IP Parking API.
Works with every AI agent you already use
…and any MCP-compatible client
Connect IP Parking MCP to OpenAI Agents SDK
Create your Vinkius account to connect IP Parking 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 gate triggers with strict OpenAI Agents SDK safety
The `control_gate` tool handles physical entry and exit barrier states directly from your agentic workflows. By deploying this tool inside the OpenAI Agents SDK, you can set up guardrails that prevent accidental openings, ensuring gates only cycle when validated by your backend logic. You configure the agent with an async context manager using `MCPServerStreamableHttp`. The agent runs pre-execution checks on the hardware status via `list_hardware` before dispatching the gate command, preventing physical damage to malfunctioning equipment.
Dynamic tariff updates via specialized agent handoffs
The `update_tariff` tool changes hourly rates and pricing caps across your parking network instantly. Using the OpenAI Agents SDK, a supervisor agent can analyze revenue dips with `get_site_status` and hand off the task to a pricing agent to execute the rate change. This handoff mechanism ensures that rate edits are isolated from general user interactions. The pricing agent pulls existing rules with `list_tariffs` to verify the new rate falls within approved bounds before committing the update. It's that simple.
Automated ANPR testing using this MCP Server
The `register_anpr` tool simulates or registers license plate recognition events directly inside your testing pipelines. Your OpenAI Agents SDK setup triggers mock entries to verify that your billing integration responds correctly to incoming vehicles. To optimize API calls during testing, set `cacheToolsList=True` in your SDK configuration. This caches the IP Parking MCP definitions, allowing the agent to process mock transactions and run `get_ticket_details` without re-fetching schemas on every run.
Set up IP Parking 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 IP Parking tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives IP Parking tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate IP Parking 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="IP Parking Agent",
instructions="You have access to IP Parking 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 IP Parking. 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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