How to Use the NASA DONKI — Space Weather Intelligence MCP in Vercel AI SDK

Q: What is the best way to render Kp index alerts from NASA DONKI — Space Weather Intelligence in Vercel AI SDK?

Use the getgeomagneticstorms endpoint within a generative UI component. The model evaluates the Kp severity and streams a styled React component back to the user, highlighting severe storms above Kp=7.

Stream real-time solar flare and geomagnetic storm telemetry directly into your React frontend with the Vercel AI SDK.

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Connect NASA DONKI — Space Weather Intelligence MCP to Vercel AI SDK

Create your Vinkius account to connect NASA DONKI — Space Weather Intelligence to Vercel AI 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 NASA DONKI — Space Weather Intelligence with Vercel AI SDK

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Stream Space Weather via MCP Server

Calling `get_solar_flares` pulls down exact classifications for C, M, and X-class solar events straight from NASA. You don't want users staring at a loading spinner while waiting to find out if an X-class flare is going to wipe out their radio communications. The Vercel AI SDK streams this classification data instantly into your UI. Your agent grabs the begin, peak, and end times alongside the detecting instruments. Because the MCP protocol handles the connection, the text generation functions push raw telemetry into your Next.js components live. Users see the active region data appear as soon as the API returns the first byte.

Map Interplanetary Shocks

The `get_interplanetary_shocks` tool tracks the CME-driven disturbances that usually hit before a major geomagnetic storm. Building a dashboard for satellite operators requires immediate visibility into these shockwaves. You can wire this endpoint to a map component that updates autonomously. Combine that with `get_geomagnetic_storms` to show the Kp index. When a storm pushes past Kp=7, your frontend can flash a severe warning without waiting for a full page reload. Developers get a direct pipeline to NASA's shock data, turning raw numbers into visual alerts.

Surface Live Notifications

Executing `get_donki_notifications` gives your application a unified feed of every recent space weather event. Instead of polling five different endpoints, you get one clean stream of CMEs, flares, and radiation spikes. That makes populating a notification tray incredibly simple. If a user needs context on a specific alert, the language model can trigger `get_cme` to pull the exact trajectory of the coronal mass ejection. Edge functions handle the parsing, keeping your client bundle small while still delivering heavy orbital telemetry.

Setup guide

Set up NASA DONKI — Space Weather Intelligence MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all NASA DONKI — Space Weather Intelligence tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent NASA DONKI — Space Weather Intelligence transactions",
});

console.log(text);
await mcpClient.close();

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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.

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Common questions about NASA DONKI — Space Weather Intelligence MCP in Vercel AI SDK

Install the @ai-sdk/mcp package in your project. Set up an HTTP transport with createMCPClient and pass the server URL. Call mcpClient.tools() and feed the results into streamText to start pulling solar data.

Yes. The SDK natively supports streaming tool calls. When your agent fetches a list of CMEs, the frontend receives the chunks immediately.

Use the get_geomagnetic_storms endpoint within a generative UI component. The model evaluates the Kp severity and streams a styled React component back to the user, highlighting severe storms above Kp=7.

Vinkius handles the underlying auth. You just need your single endpoint token for the MCP connection. The SDK passes this through the transport layer.

The server only queries public space weather telemetry, like solar energetic particle events and radiation belt enhancements. No proprietary orbital paths or private user coordinates are ever transmitted to the LLM or stored in the SDK state.

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