How to Use the AeroAPI (FlightAware) MCP in OpenAI Agents SDK

Build flight tracking agents using OpenAI Agents SDK with live AeroAPI (FlightAware) data.

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Connect AeroAPI (FlightAware) MCP to OpenAI Agents SDK

Create your Vinkius account to connect AeroAPI (FlightAware) 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 AeroAPI (FlightAware) with OpenAI Agents SDK

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Real-time flight status monitoring

Your agent checks live flight paths using `get_flight_details`. It pulls identifiers to verify current arrival times and gate changes instantly. This MCP Server provides the raw data your agent needs to trigger downstream actions. You'll avoid stale info by calling this directly within your agent loop.

Airport traffic oversight

Query specific airport activity with `list_airport_flights` to see what is landing or taking off. Use `get_airport_details` to grab ICAO or IATA metadata for precise routing. OpenAI Agents SDK handles these calls asynchronously. Your agent manages traffic flow by processing these lists without manual polling.

Health monitoring via OpenAI Agents SDK

Run `check_api_status` to confirm the connection is active before your agent kicks off a heavy task. It prevents failed requests from breaking your deployment. This tool ensures your agent logic stays robust against service downtime. It reports back immediately if the FlightAware endpoint isn't responding.

Setup guide

Set up AeroAPI (FlightAware) 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 AeroAPI (FlightAware) tools at runtime.
3

Create your Agent

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

Run the agent

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

Use the MCPServerStreamableHttp class to point your agent at the Vinkius endpoint. The SDK auto-discovers the tools so you don't have to map them by hand.

Yes. You can place validation logic around the agent's tool calls. This keeps your flight data handling safe and predictable.

Absolutely. Every flight request shows up in your OpenAI dashboard. You can inspect the inputs and outputs of every tool call.

The server returns structured data that your agent parses directly. You handle the response in your Python code as you see fit.

Vinkius isolates your traffic in a V8 sandbox. We never store your flight plan queries or specific airport identifiers once the request finishes.

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