Using a Tool
When building AI agents, you often need to integrate external data sources or functionality to enhance their capabilities. This example shows how to create an AI agent that uses a dedicated weather tool to provide accurate weather information for specific locations.
import { createTool, Agent, Mastra } from "@mastra/core";
import { z } from "zod";
interface WeatherResponse {
current: {
time: string;
temperature_2m: number;
apparent_temperature: number;
relative_humidity_2m: number;
wind_speed_10m: number;
wind_gusts_10m: number;
weather_code: number;
};
}
const weatherTool = createTool({
id: "get-weather",
description: "Get current weather for a location",
inputSchema: z.object({
location: z.string().describe("City name"),
}),
outputSchema: z.object({
temperature: z.number(),
feelsLike: z.number(),
humidity: z.number(),
windSpeed: z.number(),
windGust: z.number(),
conditions: z.string(),
location: z.string(),
}),
execute: async ({ context }) => {
return await getWeather(context.location);
},
});
const getWeather = async (location: string) => {
const geocodingUrl = `https://geocoding-api.open-meteo.com/v1/search?name=${encodeURIComponent(location)}&count=1`;
const geocodingResponse = await fetch(geocodingUrl);
const geocodingData = await geocodingResponse.json();
if (!geocodingData.results?.[0]) {
throw new Error(`Location '${location}' not found`);
}
const { latitude, longitude, name } = geocodingData.results[0];
const weatherUrl = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}¤t=temperature_2m,apparent_temperature,relative_humidity_2m,wind_speed_10m,wind_gusts_10m,weather_code`;
const response = await fetch(weatherUrl);
const data: WeatherResponse = await response.json();
return {
temperature: data.current.temperature_2m,
feelsLike: data.current.apparent_temperature,
humidity: data.current.relative_humidity_2m,
windSpeed: data.current.wind_speed_10m,
windGust: data.current.wind_gusts_10m,
conditions: getWeatherCondition(data.current.weather_code),
location: name,
};
};
function getWeatherCondition(code: number): string {
const conditions: Record<number, string> = {
0: "Clear sky",
1: "Mainly clear",
2: "Partly cloudy",
3: "Overcast",
45: "Foggy",
48: "Depositing rime fog",
51: "Light drizzle",
53: "Moderate drizzle",
55: "Dense drizzle",
56: "Light freezing drizzle",
57: "Dense freezing drizzle",
61: "Slight rain",
63: "Moderate rain",
65: "Heavy rain",
66: "Light freezing rain",
67: "Heavy freezing rain",
71: "Slight snow fall",
73: "Moderate snow fall",
75: "Heavy snow fall",
77: "Snow grains",
80: "Slight rain showers",
81: "Moderate rain showers",
82: "Violent rain showers",
85: "Slight snow showers",
86: "Heavy snow showers",
95: "Thunderstorm",
96: "Thunderstorm with slight hail",
99: "Thunderstorm with heavy hail",
};
return conditions[code] || "Unknown";
}
const weatherAgent = new Agent({
name: "Weather Agent",
instructions: `You are a helpful weather assistant that provides accurate weather information.
Your primary function is to help users get weather details for specific locations. When responding:
- Always ask for a location if none is provided
- Include relevant details like humidity, wind conditions, and precipitation
- Keep responses concise but informative
Use the weatherTool to fetch current weather data.`,
model: {
provider: "OPEN_AI",
name: "gpt-4o",
},
tools: { weatherTool },
});
const mastra = new Mastra({
agents: { weatherAgent },
});
async function main() {
const agent = await mastra.getAgent("weatherAgent");
const result = await agent.generate("What is the weather in London?");
console.log(result.text);
}
main();
View Example on GitHub