How to Use the ESA Near Earth Objects MCP in Vercel AI SDK

Q: How do I initialize the ESA Near Earth Objects MCP server with Vercel AI SDK?

Run npm install ai @ai-sdk/mcp. Then instantiate it using createMCPClient with your HTTP transport URL. Pass the result of your tools method into streamText to start pulling asteroid data.

Q: Can Vercel AI SDK stream the ESA Near Earth Objects MCP server impact table directly?

Yes. When the model invokes getimpacttable, the Vercel AI SDK streams the Palermo Scale values and impact dates directly to your UI. The user reads the risk metrics before the AI finishes generating its summary.

Q: What happens if the ESA Near Earth Objects API rate limits my Vercel AI SDK app?

You handle it in your application logic. The checkesaneoccstatus tool verifies connection health, but the framework expects you to manage retries if the ESA endpoint drops your requests.

Q: How do I query specific asteroid properties?

Your agent calls getobjectphysicalproperties with the URL-encoded designation. The SDK streams the physical properties database response straight to the edge function.

Build React and Next.js frontends that stream live asteroid telemetry using the ESA Near Earth Objects MCP server via Vercel AI SDK.

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Setup ESA Near Earth Objects with Vercel AI SDK

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Stream ESA Near Earth Objects MCP Server Risk Data

`get_risk_list` pulls the European Space Agency's active planetary defense monitor directly into your Vercel AI SDK stream. You get the object designation, estimated diameter, cumulative impact probability, and Palermo Scale value rendering in your React components as the data arrives. We don't wait for the entire JSON blob. Look, people panic over headlines. You can build an interface that immediately displays the `get_impact_table` output — rendering virtual impactors and projected dates while the model is still typing out the explanation. The user sees the actual math, not a spinning wheel.

Render Live Orbital Telemetry

`get_object_ephemerides` returns right ascension, declination, distance, and visual magnitude at specific timesteps. Hook this up to your Next.js application, and your AI client can stream right ascension coordinates directly into a client-side sky map. If you need to compute trajectories locally, `get_object_orbital_elements` grabs the raw parameters. You pass the transport URL to the MCP client, call the tools method, and let the Vercel AI SDK handle the HTTP streaming. The UI updates instantly with the asteroid's orbital arc.

Track Incoming Encounters

`get_upcoming_close_approaches` fetches the exact miss distance, date, and velocity for incoming rocks. Your Svelte or Vue frontend can display these velocity vectors dynamically. The ESA Space Safety programme updates this data multiple times a day. Frankly, historical data is just as critical for validating models. `get_recent_close_approaches` lets your users query past flyby events. They ask the agent about yesterday's encounters, and the SDK streams the exact miss distances straight to the browser. Remember to close the MCP connection when the session ends.

Setup guide

Set up ESA Near Earth Objects 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 ESA Near Earth Objects 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 ESA Near Earth Objects 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 ESA NEOCC. 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 ESA Near Earth Objects MCP in Vercel AI SDK

Run `npm install ai @ai-sdk/mcp`. Then instantiate it using `createMCPClient` with your HTTP transport URL. Pass the result of your tools method into `streamText` to start pulling asteroid data.

Yes. When the model invokes `get_impact_table`, the Vercel AI SDK streams the Palermo Scale values and impact dates directly to your UI. The user reads the risk metrics before the AI finishes generating its summary.

You handle it in your application logic. The `check_esa_neocc_status` tool verifies connection health, but the framework expects you to manage retries if the ESA endpoint drops your requests.

Your agent calls `get_object_physical_properties` with the URL-encoded designation. The SDK streams the physical properties database response straight to the edge function.

No. The Vercel AI SDK only sends the specific asteroid designations and date ranges to the server. Your users' IP addresses and browser fingerprints never touch the ESA NEOCC API.

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