# Open-Meteo Weather Scraper - Forecast & History (`scrapesage/openmeteo-scraper`) Actor

Scrape weather forecast and historical data for any list of cities or coordinates from Open-Meteo: daily and hourly temperature, precipitation, wind, humidity and more. Free source, no key, no browser.

- **URL**: https://apify.com/scrapesage/openmeteo-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** Agents, Integrations, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.55 / 1,000 forecast scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Open-Meteo Weather Scraper - Forecast & History

Get **daily weather** for any list of cities or coordinates from **Open-Meteo**. City names are geocoded
automatically, and each row is one day for one place with **max/min temperature**, **feels-like**,
**precipitation**, **rain/snow**, **wind speed & gusts**, **UV index**, **sunrise/sunset** and more.
Forecast up to 16 days ahead and up to 92 days of recent history. Free source - no key, no browser.

### What you get per location-day

| Field | Meaning |
|---|---|
| `locationName` / `country` / `region` | Resolved place |
| `latitude` / `longitude` / `timezone` / `elevation` | Coordinates and zone |
| `date` | The forecast/history day |
| `tempMax` / `tempMin` / `feelsLikeMax` / `feelsLikeMin` | Temperatures (°C) |
| `precipitationSum` / `rainSum` / `snowfallSum` / `precipProbabilityMax` | Precipitation |
| `windSpeedMax` / `windGustsMax` / `windDirection` | Wind |
| `weatherCode` / `uvIndexMax` / `sunrise` / `sunset` / `radiationSum` | Conditions |

### Input

```json
{ "locations": ["Berlin", "Tokyo", "40.71,-74.01"], "forecastDays": 7 }
```

- **Locations** - city names (geocoded automatically) or `lat,lon` coordinates, one per line.
- **Import from a file** - paste a list, or link a public `.txt`/`.csv`, a Google Sheet/Drive link, or an
  Apify key-value-store record.
- **Forecast days** (1-16) and **Past days** (0-92) set the date range. **Output fields** trim the columns.

Leave everything empty and the run returns a small free sample so you can see the shape first.

### Reliability

Reads the official [Open-Meteo API](https://open-meteo.com/en/docs) - free, no key, no proxy, no anti-bot,
plus the Open-Meteo geocoding API for place names. A run that returns nothing bills **$0**; a city that
cannot be geocoded is reported and charges nothing.

### Honest limits

- **Daily aggregates.** Each row is one day (max/min/sum values); it is not hourly or minute-level data.
- **Geocoding picks the best match** for a city name - pass `lat,lon` coordinates when you need an exact spot.

### Pricing

**$0.001 per forecast day** on the FREE tier (tiered pricing lowers it with volume). One row = one location
per day; only rows actually saved are billed.

### Output views

- **Forecast** - location, date, max/min temp, precipitation, wind and the weather code.

### Use with AI assistants (MCP)

Available through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - an agent can
pull the week's weather for a list of cities to plan logistics, travel or events.

### Agent-ready: autonomous payments (x402 & Skyfire)

This actor is **agent-ready** - AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards:

- **[x402](https://docs.apify.com/platform/integrations/x402)** - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - no account, no API key.
- **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

# Actor input Schema

## `locations` (type: `array`):

Cities or coordinates, one per line - e.g. <code>Berlin</code>, <code>Tokyo</code>, or <code>40.71,-74.01</code>. City names are geocoded automatically. <b>Leave empty and the run returns a small free sample.</b>

## `locationsFromFile` (type: `string`):

Bulk-load locations. Either <b>paste the whole list</b> (one per line), or give <b>a single link</b> to a public <code>.txt</code>/<code>.csv</code>, a Google Sheet/Drive link, or an Apify key-value-store record. A file that cannot be read says so and charges nothing.

## `forecastDays` (type: `integer`):

How many days of forecast to return per location (1-16). One row per location per day.

## `pastDays` (type: `integer`):

Also include this many recent past days (0-92) for each location.

## `outputFields` (type: `array`):

Pick the fields you want and every record is trimmed to exactly those - handy for lean CSV/Sheets exports.

## Actor input object example

```json
{
  "locations": [
    "Berlin",
    "Tokyo"
  ],
  "forecastDays": 7,
  "pastDays": 0
}
```

# Actor output Schema

## `results` (type: `string`):

Each scraped record - weather forecast rows - as a JSON item in the default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "locations": [
        "Berlin",
        "Tokyo"
    ],
    "locationsFromFile": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/openmeteo-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "locations": [
        "Berlin",
        "Tokyo",
    ],
    "locationsFromFile": "",
}

# Run the Actor and wait for it to finish
run = client.actor("scrapesage/openmeteo-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "locations": [
    "Berlin",
    "Tokyo"
  ],
  "locationsFromFile": ""
}' |
apify call scrapesage/openmeteo-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesage/openmeteo-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/djHdY4lgyFe8kYEE2/builds/6MKPQsfYRxxKzuyeW/openapi.json