How to Use the Weather (Open-Meteo) MCP in Mastra AI

Q: How does Mastra AI handle long-term weather predictions with Weather (Open-Meteo)?

Use weather.forecast for multi-day views up to 14 days out. If your workflow needs a more granular look, you should switch the tool call to weather.hourly.

Q: Can I get air quality data with Weather (Open-Meteo) and Mastra AI?

Yes, the weather.airquality tool provides current AQI and concentrations for pollutants like ozone and NO2. It always includes a specific health recommendation to guide your workflow's next action.

Q: If I need to check alerts for a multi-city trip with Mastra AI?

You combine weather.alerts (for advisories) with weather.compare. The workflow checks multiple locations and pulls any active severe weather warnings across the board.

Q: How do I get an hourly view with Weather (Open-Meteo) and Mastra AI?

For a high-precision, 24-hour look at conditions, call weather.hourly. This tool gives you the breakdown by hour, which is much better than relying on general forecasts.

Build reliable, multi-step weather workflows with Mastra AI.

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Connect Weather (Open-Meteo) MCP to Mastra AI

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Setup Weather (Open-Meteo) with Mastra AI

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Comparing Multiple Cities on the MCP Server

When you need to know 'should I go to Lisbon or Madrid this weekend?', you let `weather.compare` do the work. It takes 2 to 5 cities and computes a comfort score for each one. Mastra AI uses this tool in complex workflows, ensuring that even if the weather data fails on one endpoint, the workflow retries until it gets comparable results.

Getting Current Weather with Mastra AI

The `weather.current` tool grabs immediate conditions for any location name you give it. You can build a step that runs this check right before dispatching an itinerary email. It’s simple, direct data retrieval—perfect for the start of a reliable workflow sequence.

Forecasting Outdoor Activities using MCP Server

Need to plan a multi-day trip? `weather.best_time` analyzes 72 hours of hourly data and scores specific activities like photography or running. It doesn't just give a forecast; it suggests the optimal time window. Mastra AI can use this in a conditional step: 'IF best outdoor time is before noon, THEN notify user.' This makes your agent powerful.

Setup guide

Set up Weather (Open-Meteo) MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Weather (Open-Meteo) tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "weather-open-meteo-mcp-client",
  servers: {
    "weather-open-meteo-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Weather (Open-Meteo) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Weather (Open-Meteo) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Weather (Open-Meteo) transactions"
);
console.log(result.text);

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Common questions about Weather (Open-Meteo) MCP in Mastra AI

Use `weather.forecast` for multi-day views up to 14 days out. If your workflow needs a more granular look, you should switch the tool call to `weather.hourly`.

Yes, the `weather.air_quality` tool provides current AQI and concentrations for pollutants like ozone and NO2. It always includes a specific health recommendation to guide your workflow's next action.

This MCP Server handles atmospheric readings, including Air Quality Index values, PM2.5 concentrations, and general meteorological measurements like temperature and precipitation rates.

You combine `weather.alerts` (for advisories) with `weather.compare`. The workflow checks multiple locations and pulls any active severe weather warnings across the board.

For a high-precision, 24-hour look at conditions, call `weather.hourly`. This tool gives you the breakdown by hour, which is much better than relying on general forecasts.

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