How to Use the NASA Asteroids — Near-Earth Objects & Planetary Defense MCP in OpenAI Agents SDK

Q: How do I initialize the NASA Asteroids — Near-Earth Objects & Planetary Defense server inside my OpenAI Agents SDK project?

Install the library using pip install openai-agents and import the HTTP server class to start tracking asteroid paths. You then instantiate MCPServerStreamableHttp using your Vinkius endpoint token and pass it directly to your OpenAI Agents SDK constructor. Setting cacheToolsList=True ensures the five planetary defense tools load instantly during startup.

Q: How does this MCP integration speed up asteroid risk calculations in OpenAI Agents SDK?

By exposing tools like getneobrowse directly to your OpenAI Agents SDK agent's context, you skip writing custom API wrappers. The OpenAI Agents SDK agent inspects the asteroid catalog schema natively, allowing it to write and execute Python scripts that parse orbital velocities in real-time.

Track orbital threats safely by linking NASA Asteroids — Near-Earth Objects & Planetary Defense to your OpenAI Agents SDK pipeline.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect NASA Asteroids — Near-Earth Objects & Planetary Defense MCP to OpenAI Agents SDK

Create your Vinkius account to connect NASA Asteroids — Near-Earth Objects & Planetary Defense 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.

GDPR Free for Subscribers

Setup NASA Asteroids — Near-Earth Objects & Planetary Defense with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Monitor CNEOS Close Approaches with OpenAI Agents SDK

Your OpenAI Agents SDK pipeline uses `get_close_approaches` to identify incoming space rocks passing within critical thresholds of Earth. Instead of raw API parsing, your OpenAI Agents SDK python agent instantly consumes this clean CNEOS JSON feed to trigger automated planetary defense protocols.

Verify Fireball Events and Trajectories via MCP Server

The `get_fireballs` tool fetches atmospheric impact data directly from US government sensors to feed your OpenAI Agents SDK runtime. Setting up this MCP Server connection requires just a few lines of Python to stream fireball telemetry straight into your OpenAI Agents SDK decision loop.

Deep Catalog Lookups with Agent Guardrails

The `get_neo_lookup` tool retrieves specific orbital parameters using NASA SPK-IDs directly inside your OpenAI Agents SDK environment. Using the OpenAI Agents SDK built-in guardrails, you can verify that the asteroid ID retrieved from `get_neo_feed` matches strict planetary defense schemas before writing to your database.

Setup guide

Set up NASA Asteroids — Near-Earth Objects & Planetary Defense 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 NASA Asteroids — Near-Earth Objects & Planetary Defense tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives NASA Asteroids — Near-Earth Objects & Planetary Defense tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate NASA Asteroids — Near-Earth Objects & Planetary Defense 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="NASA Asteroids — Near-Earth Objects & Planetary Defense Agent",
            instructions="You have access to NASA Asteroids — Near-Earth Objects & Planetary Defense tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NASA. 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.

Connect NASA Asteroids — Near-Earth Objects & Planetary Defense now

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 NASA Asteroids — Near-Earth Objects & Planetary Defense MCP in OpenAI Agents SDK

Install the library using `pip install openai-agents` and import the HTTP server class to start tracking asteroid paths. You then instantiate `MCPServerStreamableHttp` using your Vinkius endpoint token and pass it directly to your OpenAI Agents SDK constructor. Setting `cacheToolsList=True` ensures the five planetary defense tools load instantly during startup.

Yes, because the OpenAI Agents SDK supports asynchronous execution within its context manager for running parallel asteroid searches. Your agent can run `get_neo_feed` to grab weekly approaches while another agent concurrently fires `get_fireballs` to log atmospheric events. The OpenAI Agents SDK framework manages these parallel requests without rate-limiting issues on your end.

The OpenAI Agents SDK's built-in tracing dashboard logs the exact payload of the failed `get_neo_lookup` call. You can inspect the SPK-ID parameter mismatch directly on your OpenAI dashboard to fix the asteroid search. This visibility lets you debug why an OpenAI Agents SDK agent attempted to fetch non-existent asteroid data.

By exposing tools like `get_neo_browse` directly to your OpenAI Agents SDK agent's context, you skip writing custom API wrappers. The OpenAI Agents SDK agent inspects the asteroid catalog schema natively, allowing it to write and execute Python scripts that parse orbital velocities in real-time.

All of your asteroid trajectory queries and fireball coordinate inputs are validated locally within your OpenAI Agents SDK environment. The Vinkius server runs inside an ephemeral, zero-trust V8 sandbox, ensuring your OpenAI Agents SDK search history is never stored or exposed to third parties.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript