How to Use the NOAA Space Weather — Solar & Geomagnetic Intelligence MCP in OpenAI Agents SDK

Q: How do I connect NOAA Space Weather — Solar & Geomagnetic Intelligence to the OpenAI Agents SDK?

Install the openai-agents package via pip. Create an MCPServerStreamableHttp instance pointing to the Vinkius endpoint and pass it to your Agent constructor. Set cacheToolsList=True so it discovers the tools instantly.

Q: Can the OpenAI Agents SDK use NOAA Space Weather — Solar & Geomagnetic Intelligence to track auroras?

Yes. Your agent can call getauroraforecast to pull the Ovation model probability map. It maps the real-time solar wind data to localized viewing chances.

Give your production agents real-time solar intelligence via the OpenAI Agents SDK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect NOAA Space Weather — Solar & Geomagnetic Intelligence MCP to OpenAI Agents SDK

Create your Vinkius account to connect NOAA Space Weather — Solar & Geomagnetic Intelligence 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 NOAA Space Weather — Solar & Geomagnetic Intelligence with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate Grid Protection with OpenAI Agents SDK

`get_dst_index` measures the ring current intensity around Earth right now. You feed this directly into your primary risk agent to monitor for storm thresholds below -100 nT. When the index drops, your agent triggers a handoff to a specialized grid-isolation agent. That second agent checks `get_solar_wind` for speeds over 500 km/s and southward Bz before executing physical hardware decoupling.

Forecast Geomagnetic Disruptions

`get_k_index_forecast` pulls the 3-day Kp index predictions straight from NOAA. Your planning agent reads this to schedule satellite orbital maneuvers or high-frequency radio blackouts. If the forecast hits a Kp of 5 or higher, the agent flags the window for potential lower-latitude aurora visibility. It validates the current state using `get_planetary_k_index` to confirm the storm actually arrived before firing off alerts.

Track Solar Flux Trends

`get_solar_flux` grabs the 10.7cm radio flux data to proxy overall solar activity. Normal quiet sun sits around 70-80 SFU, but your agent watches for spikes over 100 SFU. High flux means more sunspots and a higher chance of coronal mass ejections. You configure the OpenAI guardrails to require human approval if the agent decides to reroute flights based on this specific radiation data.

Setup guide

Set up NOAA Space Weather — Solar & Geomagnetic Intelligence 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 NOAA Space Weather — Solar & Geomagnetic Intelligence tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives NOAA Space Weather — Solar & Geomagnetic Intelligence tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate NOAA Space Weather — Solar & Geomagnetic Intelligence 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="NOAA Space Weather — Solar & Geomagnetic Intelligence Agent",
            instructions="You have access to NOAA Space Weather — Solar & Geomagnetic Intelligence 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 NOAA. 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 NOAA Space Weather — Solar & Geomagnetic Intelligence 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 NOAA Space Weather — Solar & Geomagnetic Intelligence MCP in OpenAI Agents SDK

Install the `openai-agents` package via pip. Create an `MCPServerStreamableHttp` instance pointing to the Vinkius endpoint and pass it to your Agent constructor. Set `cacheToolsList=True` so it discovers the tools instantly.

Yes. Your agent can call `get_aurora_forecast` to pull the Ovation model probability map. It maps the real-time solar wind data to localized viewing chances.

It works perfectly. You can restrict an agent from taking destructive actions based solely on `get_dst_index` readings without human review. The tracing dashboard logs exactly which NOAA metric triggered the rule.

The MCP Server handles the backoff logic. Your Python code will see a standard timeout exception, which your agent can catch and retry.

It only pulls public planetary Kp indices and solar flux data. The server never reads your proprietary grid telemetry or satellite coordinates. Your local infrastructure details stay completely inside your OpenAI environment.

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