# Météo-France Weather & Vigicrues - Official APIs (`egarian/meteo-france-weather`) Actor

Official Météo-France weather data: real-time observations from 2,000+ stations, Vigilance alerts per department, climatology series, forest fire danger. Filter by department or station. For agriculture, events, logistics, insurance.

- **URL**: https://apify.com/egarian/meteo-france-weather.md
- **Developed by:** [Loïc Rossi](https://apify.com/egarian) (community)
- **Categories:** Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 station observations

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Météo-France Weather — Official Public APIs

Official **French weather data** from Météo-France's public APIs: real-time station observations, the official Vigilance alert bulletin, historical climatology series, and seasonal forest fire danger levels.

### What it does

Four datasets, selectable via `dataTypes`:

- **`observations`** — real-time readings from 2,000+ French stations (métropole + outre-mer), 6-minute step: temperature, dew point, humidity, wind (speed/gusts/direction), precipitation, pressure, visibility, soil temperatures. Units normalized to **°C, km/h, hPa, mm**.
- **`alerts`** — the official **Vigilance** bulletin per department, for **J and J+1**: max colour per department, per-phenomenon colours (Vent, Pluie-inondation, Orages, Crues, Neige-verglas, Canicule, Grand froid, Avalanches, Vagues-submersion) with full timeline.
- **`climatologie`** — historical series per station, ordered on demand from Météo-France archives: **daily, hourly, 6-min, 10-day or monthly** step, CSV parsing included.
- **`forets`** — forest fire danger levels per department (J+1 / J+2). **Seasonal feed**: published during the forest fire campaign (~June–October); off-season the API returns no data and the actor logs an explicit note instead of failing.

### Input example

```json
{
  "dataTypes": ["observations", "alerts"],
  "departments": ["75"],
  "maxStations": 10
}
```

Climatology over a date range:

```json
{
  "dataTypes": ["climatologie"],
  "stations": ["75114001"],
  "climateStartDate": "2026-10-06",
  "climateEndDate": "2026-10-12",
  "climatePeriod": "quotidienne"
}
```

Main fields: `dataTypes`, `stations` (8-digit IDs, e.g. `75114001` = Paris-Montsouris), `departments` (e.g. `["75"]`, `["2A"]`), `maxStations`, `climateStartDate`, `climateEndDate`, `climatePeriod`, `maxRecords`.

### Output example (observation, Paris-Montsouris)

```json
{
  "dataset": "observations",
  "station_id": "75114001",
  "station_name": "PARIS-MONTSOURIS",
  "latitude": 48.821667,
  "longitude": 2.337833,
  "altitude_m": 75,
  "reference_time": "2026-10-13T08:57:05Z",
  "validity_time": "2026-10-13T08:48:00Z",
  "temperature_c": 19.2,
  "dewpoint_c": 16.1,
  "humidity_pct": 82,
  "wind_dir_deg": 270,
  "wind_speed_kmh": 11.2,
  "wind_gust_10min_kmh": 23.0,
  "precip_mm": 0.0,
  "pressure_hpa": 1013.4,
  "sea_level_pressure_hpa": 1022.6,
  "visibility_m": 20000
}
```

Output example (Vigilance alert):

```json
{
  "dataset": "vigilance",
  "domain_id": "75",
  "echeance": "J",
  "begin_validity_time": "2026-10-13T04:00:00Z",
  "end_validity_time": "2026-10-13T22:00:00Z",
  "max_color_id": 1,
  "max_color": "vert",
  "phenomena": [
    {
      "phenomenon_id": 1,
      "phenomenon": "Vent",
      "max_color_id": 1,
      "max_color": "vert",
      "timeline": [{ "begin_time": "...", "end_time": "...", "color": "vert" }]
    }
  ]
}
```

### Data source & authentication

- Source: **Météo-France public APIs** — `https://public-api.meteofrance.fr` (official French national weather service).
- Requires a **free API key**: create it at [portail-api.meteofrance.fr](https://portail-api.meteofrance.fr) and subscribe to the public APIs (DonneesPubliquesObservation, DonneesPubliquesVigilance, DonneesPubliquesClimatologie, DonneesPubliquesMeteoForets).
- The actor sends the key in the **`apikey` HTTP header** (Météo-France's custom scheme, not Bearer). Set it as the `METEOFRANCE_API_KEY` environment variable / Apify secret — never in code.

### Notes

- Vigilance colour codes: 1 = vert (green), 2 = jaune (yellow), 3 = orange, 4 = rouge (red).
- Coastal departments may carry an extra sub-zone domain (e.g. `7510`); department filters include it automatically.
- Quotas: the free tier allows 50–100 requests/minute per API; the actor caps stations per run (`maxStations`) to stay well within limits.
- Forest fire feed is seasonal; expect zero `forets` records outside the campaign.

# Actor input Schema

## `cities` (type: `array`):

City names

## `departments` (type: `array`):

Department codes

## `coordinates` (type: `array`):

Lat/Lon pairs \[{lat, lon}]

## `dataTypes` (type: `array`):

Types of data to fetch

## `days` (type: `integer`):

Number of forecast days

## `maxRecords` (type: `integer`):

Safety limit

## `outputFields` (type: `string`):

Output verbosity

## Actor input object example

```json
{
  "cities": [],
  "departments": [
    "75"
  ],
  "coordinates": [],
  "dataTypes": [
    "observations",
    "alerts"
  ],
  "days": 7,
  "maxRecords": 1000,
  "outputFields": "standard"
}
```

# Actor output Schema

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

Météo-France observations, Vigilance alerts, climatology series or forest fire danger (one item per row of the requested mode).

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("egarian/meteo-france-weather").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("egarian/meteo-france-weather").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 '{}' |
apify call egarian/meteo-france-weather --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,egarian/meteo-france-weather"
        }
    }
}
```

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/P7JX94g7XvnhoJTKN/builds/Knfa7LFnTaINAgygK/openapi.json