# French Property Scraper — Bien'ici Annonces Immo (MCP) (`amygraphics/france-real-estate-scraper`) Actor

French property scraper (Bien'ici): annonces immo France — appartements et maisons à vendre ou à louer, prix, prix/m², surface, DPE, photos, agence. France real estate listings data. MCP-ready for AI agents.

- **URL**: https://apify.com/amygraphics/france-real-estate-scraper.md
- **Developed by:** [Zakaria el bouami](https://apify.com/amygraphics) (community)
- **Categories:** Real estate
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 listing extracteds

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

## French Property Scraper — Bien'ici Annonces Immo (MCP)

Extract **clean, structured French property listings** — for sale or for rent — from **Bien'ici.com**, one of France's largest real-estate portals. One Actor, no browser, no proxy.

Part of the *data franchise* series by the same developer: 🇲🇦 Avito.ma & Mubawab.ma (Morocco) • 🇫🇷 Paruvendu.fr (France).

### What you get

One JSON row per property, ready for analysis, CSV/Excel export or AI pipelines:

| Field group | Examples |
|---|---|
| Identification | `id`, `url`, `reference`, `title`, `description` |
| Price | `price`, `currency`, `pricePerSquareMeter`, `priceWithoutFees`, `priceHasDecreased` |
| Location | `city`, `postalCode`, `departmentCode`, `district`, `latitude`, `longitude` |
| Property | `propertyType`, `surfaceArea`, `rooms`, `bedrooms`, `floor`, `yearOfConstruction`, `heating`, `exposition` |
| Energy | `energyClass` (DPE A–G), `gesClass` (GES A–G) |
| Market signals | `publicationDate`, `modificationDate`, `newProperty`, `isExclusiveSaleMandate`, `sellerType` |
| Media | `photosCount`, `mainPhoto` |
| Agency (optional) | `agencyName`, `agencyPhone`, `agencyAddress` |

### How to use

1. Set **Locations** — a city (`Paris`), an arrondissement (`Paris 15e`, `Lyon 3e`) or a department (`Hauts-de-Seine`).
2. Pick **buy** or **rent**, optionally add property types, budget, surface and rooms.
3. Set **Max listings**, press **Start** and export your dataset.

Example inputs:

```json
{ "locations": ["Paris", "Lyon 3e"], "transactionType": "buy", "propertyTypes": ["flat"], "minPrice": 200000, "maxPrice": 600000, "maxResults": 500 }
```

```json
{ "locations": ["Hauts-de-Seine"], "transactionType": "rent", "maxPrice": 1500, "maxResults": 1000, "enrichAgencyDetails": true }
```

### Use cases

- 🏠 Market analysis: price per m² by city, arrondissement or district
- 📉 Price-drop and time-on-market monitoring
- ⚡ Energy-transition analysis using DPE/GES ratings
- 🤖 Valuation models, proptech apps and AI data pipelines
- 🏢 Agency lead data (with `enrichAgencyDetails`)

### Use from AI agents (MCP)

This Actor is exposed as a tool through **Apify's MCP server** — any MCP client (Claude, Cursor, VS Code / Copilot, Codex, custom agents) can discover and run it without writing code:

```json
{
  "mcpServers": {
    "apify": { "url": "https://mcp.apify.com?tools=amygraphics/france-real-estate-scraper" }
  }
}
```

Then just ask: *"Use amygraphics/france-real-estate-scraper to get me this data."* Agents can also pay autonomously — this Actor is **whitelisted for agentic payments** (Direct x402 / Apify AGI prepaid token), so no Apify account is required.

### Pricing

Pay-per-event: one **`listing-extracted`** charge per successfully extracted listing, plus a tiny **`apify-actor-start`** fee per run. Failed pages and empty searches are never charged, and the Actor stops cleanly when your spending limit is reached.

### Notes & limits

- The portal paginates up to 2 400 results per query — combine several locations or filters for deeper coverage.
- Coordinates are the portal's approximate (privacy-blurred) positions.
- This Actor reads publicly available data only.

***

### 🇫🇷 En français

Extrait des **annonces immobilières françaises structurées** (vente ou location) depuis **Bien'ici.com** : prix, prix au m², surface, pièces, classe DPE/GES, photos, coordonnées approximatives, type de vendeur, date de publication — et, en option, les coordonnées de l'agence.

Filtrez par ville, arrondissement ou département, budget, surface et nombre de pièces. Export JSON/CSV/Excel direct. Tarification à l'annonce extraite (`listing-extracted`) ; les pages en échec ne sont jamais facturées, et l'Actor s'arrête proprement quand votre limite de dépense est atteinte.

Fait partie de la série *data franchise* du même développeur : 🇲🇦 Maroc (Avito.ma, Mubawab.ma) • 🇫🇷 France (Paruvendu.fr, Bien'ici.com).

***

### Agents IA (MCP)

Cet Actor est exposé comme outil du serveur **MCP d'Apify** — branchez `https://mcp.apify.com?tools=amygraphics/france-real-estate-scraper` dans Claude, Cursor, VS Code ou Codex, puis demandez vos données en langage naturel. Les agents peuvent payer seuls (x402 / AGI) : l'Actor est *whitelisted* pour les paiements agentiques.

# Actor input Schema

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

French places to search: city ('Paris'), arrondissement ('Paris 15e', 'Lyon 3e'), or department ('Hauts-de-Seine', 'Bouches-du-Rhône').

## `transactionType` (type: `string`):

Search for properties for sale (buy) or rentals (rent).

## `propertyTypes` (type: `array`):

Leave empty for all types. Accepted values: flat, house, terrain, castle, premises, building, parking, loft, townhouse.

## `minPrice` (type: `integer`):

Minimum price in euros.

## `maxPrice` (type: `integer`):

Maximum price in euros.

## `minArea` (type: `integer`):

Minimum living surface in square metres.

## `maxArea` (type: `integer`):

Maximum living surface in square metres.

## `minRooms` (type: `integer`):

Minimum number of rooms (pièces).

## `maxRooms` (type: `integer`):

Maximum number of rooms (pièces).

## `minBedrooms` (type: `integer`):

Minimum number of bedrooms.

## `maxBedrooms` (type: `integer`):

Maximum number of bedrooms.

## `sortBy` (type: `string`):

Order in which listings are returned by the portal.

## `sortOrder` (type: `string`):

Ascending or descending order for the selected sort.

## `maxResults` (type: `integer`):

Maximum number of listings to extract in this run. One billable event per extracted listing.

## `enrichAgencyDetails` (type: `boolean`):

Fetch each listing's detail page to add the agency name, phone and office address. Slower (one extra request per listing) but richer output.

## `chargedEventName` (type: `string`):

Pay-per-event name charged for each successfully extracted listing.

## Actor input object example

```json
{
  "locations": [
    "Paris"
  ],
  "transactionType": "buy",
  "propertyTypes": [],
  "sortBy": "publicationDate",
  "sortOrder": "desc",
  "maxResults": 100,
  "enrichAgencyDetails": false,
  "chargedEventName": "listing-extracted"
}
```

# Actor output Schema

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

No description

# 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": [
        "Paris"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("amygraphics/france-real-estate-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": ["Paris"] }

# Run the Actor and wait for it to finish
run = client.actor("amygraphics/france-real-estate-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": [
    "Paris"
  ]
}' |
apify call amygraphics/france-real-estate-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,amygraphics/france-real-estate-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/dkcdNpIx9E7YD7p83/builds/PKeuh5eRIkhKd9m3e/openapi.json