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Open Meteo Scraper

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Pay per event

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Open Meteo Scraper

Open Meteo Scraper

Get weather forecasts, current conditions, and historical data for any location worldwide. Supports daily and hourly data with customizable units. No API key needed.

Pricing

Pay per event

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Developer

Stas Persiianenko

Stas Persiianenko

Maintained by Community

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0

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3

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2

Monthly active users

14 hours ago

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Open-Meteo Weather Scraper

Get weather forecasts and current conditions for any location worldwide using the Open-Meteo API. No API key required.

What does Open-Meteo Weather Scraper do?

This actor fetches real-time weather data and forecasts for one or more locations. It uses the Open-Meteo free weather API — one of the most accurate open-source weather services available — and returns structured data including:

  • Current conditions: temperature, feels-like temperature, humidity, weather description, precipitation, cloud cover, pressure
  • Wind data: speed, direction, gusts in your preferred unit (km/h, mph, m/s, knots)
  • UV & daylight: UV index, sunrise/sunset times, sunshine duration
  • Daily forecasts: up to 16 days ahead with min/max temperatures, precipitation probability, and weather codes
  • Hourly data: optional hour-by-hour breakdown for detailed analysis
  • Smart geocoding: accepts city names or latitude/longitude coordinates

Why use Open-Meteo Weather Scraper?

  • No API key needed — Open-Meteo is free for non-commercial use with no signup required
  • Global coverage — weather data for any location on Earth with ~1km resolution
  • High accuracy — combines data from national weather services including DWD, NOAA, and Météo-France
  • Up to 16-day forecasts — detailed daily and optional hourly predictions
  • Multiple locations — fetch weather for many cities in a single run
  • Flexible units — choose Celsius/Fahrenheit, km/h/mph/m/s/knots
  • Human-readable weather — WMO weather codes translated to plain English descriptions

Use cases

  • Travel planning: Check weather forecasts for upcoming trip destinations
  • Agriculture: Monitor temperature, precipitation, and UV for crop management
  • Event planning: Get multi-day forecasts for outdoor event scheduling
  • Supply chain: Weather-aware logistics and demand forecasting
  • Energy: Solar and wind forecasting for renewable energy planning
  • Retail analytics: Correlate sales data with weather conditions
  • Research: Collect weather data across multiple locations for analysis

How to get weather data with Open-Meteo Scraper

  1. Go to Open-Meteo Weather Scraper on Apify Store.
  2. Enter one or more locations — city names (e.g., "London") or coordinates (e.g., "48.8566,2.3522").
  3. Set the number of forecast days (0–16). Use 0 for current weather only.
  4. Optionally enable hourly data for detailed hour-by-hour forecasts.
  5. Choose your preferred temperature and wind speed units.
  6. Click Start and download your data as JSON, CSV, or Excel.

Input parameters

ParameterTypeDescription
locationsArrayList of locations — city names or "lat,lon" coordinates (required)
forecastDaysIntegerForecast days to include, 0–16 (default: 7)
includeHourlyBooleanInclude hourly data for each forecast day (default: false)
temperatureUnitString"celsius" or "fahrenheit" (default: "celsius")
windSpeedUnitString"kmh", "mph", "ms", or "kn" (default: "kmh")

Output example

Each location in the dataset contains current conditions and daily forecasts:

{
"location": "London, United Kingdom",
"latitude": 51.5085,
"longitude": -0.1257,
"elevation": 27.0,
"timezone": "Europe/London",
"country": "United Kingdom",
"temperature": 14.2,
"apparentTemperature": 12.8,
"humidity": 72,
"weatherCode": 3,
"weatherDescription": "Overcast",
"precipitation": 0.0,
"windSpeed": 15.3,
"windDirection": 220,
"windGusts": 28.1,
"cloudCover": 100,
"pressure": 1018.5,
"uvIndex": 2.1,
"isDay": true,
"currentTime": "2026-03-03T14:00",
"temperatureUnit": "°C",
"windSpeedUnit": "kmh",
"dailyForecast": [
{
"date": "2026-03-03",
"weatherCode": 3,
"weatherDescription": "Overcast",
"temperatureMax": 14.2,
"temperatureMin": 8.1,
"temperatureMean": 11.2,
"precipitationSum": 0.0,
"precipitationProbabilityMax": 10,
"windSpeedMax": 22.5,
"uvIndexMax": 2.5,
"sunrise": "2026-03-03T06:42",
"sunset": "2026-03-03T17:48",
"sunshineDuration": 18200
}
],
"hourlyData": [],
"scrapedAt": "2026-03-03T14:00:00.000Z"
}

How much does it cost to get weather data from Open-Meteo?

Open-Meteo Weather Scraper uses a pay-per-event pricing model:

EventPrice
Run started$0.001
Per location fetched$0.001

Cost examples:

  • 5 locations: $0.001 + (5 × $0.001) = $0.006
  • 20 locations: $0.001 + (20 × $0.001) = $0.021
  • 100 locations: $0.001 + (100 × $0.001) = $0.101

API usage

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('YOUR_USERNAME/open-meteo-scraper').call({
locations: ['London', 'Paris', 'Berlin'],
forecastDays: 7,
temperatureUnit: 'celsius',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(w => {
console.log(`${w.location}: ${w.temperature}${w.temperatureUnit} - ${w.weatherDescription}`);
});

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_API_TOKEN')
run = client.actor('YOUR_USERNAME/open-meteo-scraper').call(run_input={
'locations': ['London', 'Paris', 'Berlin'],
'forecastDays': 7,
'temperatureUnit': 'celsius',
})
dataset = client.dataset(run['defaultDatasetId']).list_items().items
for w in dataset:
print(f"{w['location']}: {w['temperature']}{w['temperatureUnit']} - {w['weatherDescription']}")

cURL

curl "https://api.apify.com/v2/acts/automation-lab~open-meteo-scraper/runs" \
-X POST \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"locations": ["London", "Paris", "Berlin"], "forecastDays": 7, "temperatureUnit": "celsius"}'

Integrations

Connect Open-Meteo Weather Scraper with other tools using Apify integrations:

  • Google Sheets — Export weather data to spreadsheets for monitoring and analysis
  • Slack / Email — Get weather alerts when conditions change
  • Webhooks — Trigger workflows based on weather data updates
  • Zapier / Make — Connect to 5,000+ apps for weather-driven automation
  • Amazon S3 / Google Cloud — Archive weather data for long-term analysis

Tips and best practices

  • City names vs coordinates — city names are geocoded automatically; for precision, use "lat,lon" format
  • Forecast days — set to 0 for current weather only; up to 16 days available
  • Hourly data — produces detailed output but significantly more data; disable if you only need daily summaries
  • Multiple locations — add as many locations as needed; each is fetched in a single API call
  • Weather codes — WMO standard codes (0–99) are automatically translated to human-readable descriptions
  • Scheduling — set up recurring runs on Apify to build weather history datasets

Weather code reference

CodeDescription
0Clear sky
1–3Mainly clear, Partly cloudy, Overcast
45, 48Fog, Depositing rime fog
51–55Drizzle (light, moderate, dense)
61–65Rain (slight, moderate, heavy)
71–75Snowfall (slight, moderate, heavy)
80–82Rain showers (slight, moderate, violent)
95–99Thunderstorm, with hail

Data source

All weather data comes from Open-Meteo, which aggregates data from national weather services worldwide. Data is available under the CC BY 4.0 license.

Use with AI agents via MCP

Open-Meteo Weather Scraper is available as a tool for AI assistants via the Model Context Protocol (MCP).

Setup for Claude Code

$claude mcp add --transport http apify "https://mcp.apify.com"

Setup for Claude Desktop, Cursor, or VS Code

{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com"
}
}
}

Example prompts

  • "Get weather forecast for London this week"
  • "What's the temperature and precipitation forecast for Tokyo?"

Learn more in the Apify MCP documentation.

Legality

Scraping publicly available data is generally legal according to the US Court of Appeals ruling (HiQ Labs v. LinkedIn). This actor only accesses publicly available information and does not require authentication. Always review and comply with the target website's Terms of Service before scraping. For personal data, ensure compliance with GDPR, CCPA, and other applicable privacy regulations.

FAQ

Q: Is an API key needed? A: No. Open-Meteo provides free weather data without authentication for non-commercial use.

Q: How accurate are the forecasts? A: Open-Meteo uses high-resolution models (1–11km) from DWD, NOAA, Météo-France, and other national services. Short-term forecasts (1–3 days) are highly accurate.

Q: Can I get historical weather data? A: This actor focuses on current conditions and forecasts (up to 16 days). Historical data requires the Open-Meteo archive API which may have usage restrictions.

Q: What happens if a location can't be found? A: The actor logs a warning and skips unresolvable locations. Other locations in the same run are still processed.

Q: The weather data seems wrong for my city — what should I check? A: City name geocoding may resolve to a different location with the same name. For precise results, use latitude/longitude coordinates instead (e.g., "48.8566,2.3522" for Paris). Check the returned latitude and longitude fields to verify the resolved location.

Q: Hourly data is empty even though I set includeHourly: true — why? A: Make sure forecastDays is set to at least 1. If forecastDays is 0 (current weather only), there are no forecast days to generate hourly breakdowns for.

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