# ImmoScout24 Property Detail Scraper (`good-apis/immoscout24-detail-scraper`) Actor

- **URL**: https://apify.com/good-apis/immoscout24-detail-scraper.md
- **Developed by:** [Danny](https://apify.com/good-apis) (community)
- **Categories:** Real estate
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 results

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/platform/actors/running/actors-in-store#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

## ImmoScout24 Property Detail Scraper

Get the **full detail** of a single **ImmobilienScout24** (Germany) listing by its id or URL — rent
breakdown or purchase price, living area, rooms, year built, condition, heating, features (balcony /
lift / cellar / kitchen …), the realtor, every photo, and the full description text. Leave the id
blank and the actor returns a currently-live listing from a region you choose (handy for testing).

**Pricing:** $1.00 per 1,000 results (pay-per-result). One listing = one result.

### What you get

```json
{
  "id": "169446368",
  "url": "https://www.immobilienscout24.de/expose/169446368",
  "title": "Exklusiv für Studis/Azubis - helles Zimmer in einer 3er-WG",
  "address": "Roedernallee 118H, 13437 Wittenau, Berlin",
  "city": "Berlin",
  "zip_code": "13437",
  "district": "Wittenau",
  "lat": 52.58927,
  "lon": 13.33861,
  "real_estate_type": "apartmentrent",
  "base_rent": 380,
  "total_rent": 475.51,
  "service_charge": 95.51,
  "purchase_price": null,
  "area_sqm": 27.83,
  "rooms": 1,
  "year_built": 1975,
  "condition": "well_kept",
  "heating_type": "central_heating",
  "features": {"balcony": true, "lift": false, "cellar": true, "built_in_kitchen": true},
  "image_count": 11,
  "images": ["https://pictures.immobilienscout24.de/..."],
  "realtor": {"name": "Gesobau Vermietungsteam", "company": "GESOBAU AG", "rating": 4.3},
  "description": "### Objektbeschreibung\n..."
}
```

### Input

| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `expose_id` | string | no\* | ImmoScout24 listing id — the number in an expose URL, e.g. `169316363`. |
| `url` | string | no\* | Full listing URL, e.g. `https://www.immobilienscout24.de/expose/169316363`. Alternative to `expose_id`. |
| `seed_region` | string | no | Used only when `expose_id` and `url` are both blank: returns a live apartment-for-rent listing from this region path (e.g. `/de/berlin/berlin`, `/de/bayern/muenchen`). Default `/de/berlin/berlin`. |

\* Provide `expose_id` **or** `url` for a specific listing; if neither is given the actor uses
`seed_region` to return a currently-live listing.

#### Output fields

| Field | Description |
|-------|-------------|
| `id`, `url` | Listing id and URL |
| `title` | Listing headline |
| `address`, `street`, `house_number`, `zip_code`, `city`, `district` | Location |
| `lat`, `lon` | Coordinates |
| `real_estate_type` | Property type |
| `base_rent`, `total_rent`, `service_charge` | Rent breakdown in EUR (rentals) |
| `purchase_price` | Purchase price in EUR (sales) |
| `area_sqm`, `rooms`, `year_built` | Size, rooms, construction year |
| `condition`, `interior_quality`, `heating_type`, `firing_types` | Condition & heating |
| `features` | Object: `balcony`, `lift`, `cellar`, `built_in_kitchen`, `newly_constructed`, `garden`, `pets_allowed` |
| `image_count`, `images` | Photo count and up to 20 photo URLs |
| `realtor` | Object: `name`, `company`, `rating` |
| `description` | Full listing description (Markdown) |

### Usage — Python

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("good-apis/immoscout24-detail-scraper").call(run_input={
    "expose_id": "169446368"
})
item = next(client.dataset(run["defaultDatasetId"]).iterate_items())
print(item["title"], item["total_rent"], item["area_sqm"], item["rooms"])
```

### Usage — Node.js

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

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('good-apis/immoscout24-detail-scraper').call({
    url: 'https://www.immobilienscout24.de/expose/169446368',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);
```

### Tips

- Get listing ids in bulk from the companion **ImmoScout24 Property Search Scraper**, then feed each
  `id` here for full detail.
- Rentals populate `base_rent` / `total_rent`; sales populate `purchase_price`. Whichever the listing
  carries is filled, the other is `null`.

### FAQ

**What if the listing was removed?** ImmoScout24 returns 404 for a delisted expose; the actor reports a
clear "not found" and no result is charged.

**Rent or price?** The field depends on the listing: `total_rent`/`base_rent` for rentals,
`purchase_price` for sales.

**Which country?** immobilienscout24.**de** (Germany).

# Actor input Schema

## `expose_id` (type: `string`):

ImmobilienScout24 listing (expose) id — the number in an expose URL, e.g. '169316363'. Leave blank to auto-pick a live listing from the sample region below.

## `url` (type: `string`):

Full ImmoScout24 listing URL, e.g. 'https://www.immobilienscout24.de/expose/169316363'. Alternative to the listing id.

## `seed_region` (type: `string`):

Only used when the ID and URL are both blank: the actor returns the full detail of a live apartment-for-rent listing in this ImmoScout24 region path, e.g. '/de/berlin/berlin' or '/de/bayern/muenchen'. This lets the actor always return a currently-live listing.

## Actor input object example

```json
{
  "seed_region": "/de/berlin/berlin"
}
```

# Actor output Schema

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

All scraped items 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 = {
    "seed_region": "/de/berlin/berlin"
};

// Run the Actor and wait for it to finish
const run = await client.actor("good-apis/immoscout24-detail-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 = { "seed_region": "/de/berlin/berlin" }

# Run the Actor and wait for it to finish
run = client.actor("good-apis/immoscout24-detail-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "seed_region": "/de/berlin/berlin"
}' |
apify call good-apis/immoscout24-detail-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=good-apis/immoscout24-detail-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Uj1CTIEYjJneIolKC/builds/1dhInkWflYsuXDF93/openapi.json