How to Use the INMET (Apitempo - Meteorologia) MCP in Vercel AI SDK

Q: Can Vercel AI SDK handle the volume of data from INMET (Apitempo - Meteorologia)?

Yes. Since you only call the specific tools you need, like getstationdatadaily, you keep the payload light. The SDK manages the stream efficiently.

Stream official Brazilian weather data directly into your Vercel AI SDK interface for real-time, data-driven UI updates.

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Connect INMET (Apitempo - Meteorologia) MCP to Vercel AI SDK

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Setup INMET (Apitempo - Meteorologia) with Vercel AI SDK

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Real-time forecast streaming with AI SDK

Feed your UI live weather updates by hooking `get_all_forecasts` or `get_forecast_by_city` directly into your streaming response. Your users see the forecast populate as the model generates the text. This bypasses the need for static loading screens. The data flows from the server to your component state without manual parsing overhead.

Visualizing satellite data in Vercel AI SDK

Fetch current GOES-16 imagery using `get_satellite_images` to show live cloud cover in your frontend. The binary data maps straight to your image components. Your application handles the raw response immediately. It provides a visual layer that standard text-based weather reports simply cannot match.

Precision station data for Vercel AI SDK apps

Query specific sensor readings with `get_station_data_hourly` to build detailed weather dashboards. You get exact telemetry points for any station defined in `list_stations`. This gives your frontend granular control over historical and current conditions. You define the resolution of the data shown to the user.

Setup guide

Set up INMET (Apitempo - Meteorologia) 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 INMET (Apitempo - Meteorologia) 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 INMET (Apitempo - Meteorologia) transactions",
});

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

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Common questions about INMET (Apitempo - Meteorologia) MCP in Vercel AI SDK

Install the MCP client packages and point your transport to the server URL. Use the generated tools within your streamText or generateText calls to pull weather data.

Yes. Since you only call the specific tools you need, like `get_station_data_daily`, you keep the payload light. The SDK manages the stream efficiently.

It does. The MCP server communication happens over standard HTTP, making it compatible with the edge runtime environment for fast responses.

It provides official government-validated information. You get the same data the national agency publishes for public use.

Your AI client only exchanges specific query parameters like station IDs. The connection is ephemeral and strictly scoped to the tools you invoke.

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