What Kp level is needed to see aurora?

Kp ≥ 5: visible from northern US/southern Canada. Kp ≥ 7: visible from mid-latitudes (40°N). Kp = 9: rare — aurora visible from southern US/Europe. Check the Ovation model for precise probability at your location.

NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: NOAA Space Weather — Solar & Geomagnetic Intelligence
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect NOAA Space Weather — Solar & Geomagnetic Intelligence through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to NOAA Space Weather — Solar & Geomagnetic Intelligence "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in NOAA Space Weather — Solar & Geomagnetic Intelligence?"
    )
    print(result.data)

asyncio.run(main())

NOAA Space Weather — Solar & Geomagnetic Intelligence

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server

Real-time space weather from NOAA's Space Weather Prediction Center.

Pydantic AI validates every NOAA Space Weather — Solar & Geomagnetic Intelligence tool response against typed schemas, catching data inconsistencies at build time. Connect 6 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Kp Index — Current geomagnetic activity (aurora threshold)
Kp Forecast — 3-day predictions
Solar Wind — Speed (km/s) and Bz from DSCOVR satellite
Aurora Forecast — Ovation probability model (global)
Solar Flux — F10.7 solar activity proxy
Dst Index — Ring current storm intensity

Who Needs This?

Aurora hunters, satellite operators, HF radio operators, power grid managers, airline operators (polar routes), and space enthusiasts.

The NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect NOAA Space Weather — Solar & Geomagnetic Intelligence to Pydantic AI via MCP

Follow these steps to integrate the NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 6 tools from NOAA Space Weather — Solar & Geomagnetic Intelligence with type-safe schemas

Why Use Pydantic AI with the NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server

Pydantic AI provides unique advantages when paired with NOAA Space Weather — Solar & Geomagnetic Intelligence through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your NOAA Space Weather — Solar & Geomagnetic Intelligence integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your NOAA Space Weather — Solar & Geomagnetic Intelligence connection logic from agent behavior for testable, maintainable code

NOAA Space Weather — Solar & Geomagnetic Intelligence + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server delivers measurable value.

Type-safe data pipelines: query NOAA Space Weather — Solar & Geomagnetic Intelligence with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple NOAA Space Weather — Solar & Geomagnetic Intelligence tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query NOAA Space Weather — Solar & Geomagnetic Intelligence and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock NOAA Space Weather — Solar & Geomagnetic Intelligence responses and write comprehensive agent tests

NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect NOAA Space Weather — Solar & Geomagnetic Intelligence to Pydantic AI via MCP:

get_aurora_forecast

Powered by real-time solar wind data. The gold standard for aurora forecasting worldwide. Get the aurora probability forecast map data (Ovation model)

get_dst_index

Measures the intensity of the ring current around Earth. Values below -50 nT indicate a moderate storm, below -100 nT a strong storm, below -250 nT a severe storm. Critical for satellite operators and power grid monitoring. Get the Dst index — real-time geomagnetic storm intensity

get_k_index_forecast

Use this to plan for aurora viewing, satellite vulnerabilities, or HF radio propagation impacts. Get the 3-day Kp index forecast — predicted geomagnetic activity

get_planetary_k_index

Kp ranges 0-9. Values ≥5 indicate geomagnetic storms with visible aurora at lower latitudes. Updated every 3 hours. Essential for aurora hunters, satellite operators, and power grid managers. Get the NOAA Planetary K-index — geomagnetic activity and aurora probability

get_solar_flux

7 solar flux index. Higher values (>100 SFU) indicate increased solar activity, more sunspots, and higher probability of solar flares and CMEs. Normal quiet-sun values are 70-80 SFU. Get the 10.7cm solar radio flux — a proxy for solar activity level

get_solar_wind

The solar wind drives geomagnetic storms — when speed exceeds 500 km/s with southward Bz, aurora probability increases dramatically. Get real-time solar wind speed and magnetic field conditions

Example Prompts for NOAA Space Weather — Solar & Geomagnetic Intelligence in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with NOAA Space Weather — Solar & Geomagnetic Intelligence immediately.

"Can I see the aurora tonight?"

"What is the current solar wind status?"

Troubleshooting NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server with Pydantic AI

Common issues when connecting NOAA Space Weather — Solar & Geomagnetic Intelligence to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

NOAA Space Weather — Solar & Geomagnetic Intelligence + Pydantic AI FAQ

Common questions about integrating NOAA Space Weather — Solar & Geomagnetic Intelligence MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your NOAA Space Weather — Solar & Geomagnetic Intelligence MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.