How to Use the AerisWeather MCP in Vercel AI SDK

Q: Can the Vercel AI SDK handle batched AerisWeather requests?

Yes. Your agent can call getbatch to combine up to 31 distinct weather queries like forecasts and alerts into a single call. This keeps your edge function execution times low.

Q: How do I map location coordinates to weather data?

Your agent uses getplaces to find the correct geographical ID for a city or airport. Then, it passes that ID to getobservations to pull the current weather.

Feed real-time AerisWeather data directly into your Vercel AI SDK streaming interfaces without loading spinners.

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Connect AerisWeather MCP to Vercel AI SDK

Create your Vinkius account to connect AerisWeather 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 AerisWeather with Vercel AI SDK

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Feed live weather alerts into React views via MCP Server

Your Next.js app needs to show active weather warnings without freezing the UI. This MCP Server lets your Vercel AI SDK client call `get_alerts` to grab active warnings instantly. Because the SDK supports direct streaming, the tool output flows straight to your component. Your users see active advisories update live instead of staring at a blank loading state.

Batch weather observations for high-speed edge rendering

Fetching weather data for multiple locations usually kills performance. This client lets you bundle up to 31 location requests into a single roundtrip using `get_batch`. Running this on Vercel Edge Functions means zero cold-start lag. The MCP client packages the coordinates, hits the endpoint, and renders the batched observations in one smooth motion.

Deliver minute-by-minute rain forecasts to your UI

When users want to know if it will rain in ten minutes, latency matters. Use `get_conditions` with the Vercel AI SDK to pull minutely precipitation forecasts instantly. The client processes the geographic coordinates from `get_places` and passes them to the weather engine. Your interface displays the exact precipitation window without any backend middleware.

Setup guide

Set up AerisWeather 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 AerisWeather 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 AerisWeather 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 AerisWeather. 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 AerisWeather MCP in Vercel AI SDK

Set up the MCP client using createMCPClient and pass the tools directly to streamText. Don't forget to call close when the session ends to prevent memory leaks.

Yes. Your agent can call get_batch to combine up to 31 distinct weather queries like forecasts and alerts into a single call. This keeps your edge function execution times low.

Yes. The server runs in a secure sandbox that connects to your Vercel AI SDK setup via standard transport protocols. It works perfectly within Next.js edge routes.

Your agent uses get_places to find the correct geographical ID for a city or airport. Then, it passes that ID to get_observations to pull the current weather.

All location IDs and coordinate lookups sent to this server are processed in isolated, ephemeral sandboxes. No search history or geographic coordinates are stored or used for training.

Use it with your favorite AI tools

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