# Funda.nl Scraper 🏠 (`easyapi/funda-nl-scraper`) Actor

Scrape property listings from Funda.nl - Extract detailed real estate data including prices, locations, property features, and more. Perfect for real estate analysis and market research in the Netherlands.

- **URL**: https://apify.com/easyapi/funda-nl-scraper.md
- **Developed by:** [EasyApi](https://apify.com/easyapi) (community)
- **Categories:** Real estate, Integrations
- **Features:** Limited permissions
- **Stats:** 397 total users, 8 monthly users, 96.5% runs succeeded, 7 bookmarks
- **User rating**: 3.66 out of 5 stars

## Pricing

from $4.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Funda.nl Scraper 🏠

### 🔍 What does Funda.nl Scraper do?

This actor scrapes real estate listings from Funda.nl or Fundainbusiness.nl, the Netherlands' leading property website. It extracts comprehensive property data, enabling you to gather valuable real estate market insights.

### ✨ Features

- 🏘️ Scrapes detailed property listings from search results
- 📊 Extracts comprehensive property information
- 🔄 Supports pagination and dynamic loading
- 🚀 High-performance with built-in proxy rotation
- ⚡ Handles rate limiting and anti-bot measures
- 💾 Outputs structured JSON data

### 🎯 Use Cases

- 📈 Real estate market analysis
- 🏢 Property investment research
- 💰 Price trend monitoring
- 🗺️ Geographic market analysis
- 📊 Data aggregation for real estate platforms

### 💡 Input Parameters

The actor accepts the following input parameters:

- `searchUrls` (Required): Array of Funda.nl search URLs to scrape
- `maxItems` (Optional): Maximum number of items to scrape
- `proxyConfiguration` (Optional): Proxy settings for the scraper

### 📝 Output Format

The actor outputs data in JSON format, including:

- Property details (price, location, size)
- Property features and amenities
- Listing information
- Images and media links
- Agent contact information

### 🔨 Usage

1. Input your Funda.nl or Fundainbusiness.nl search URL(s)
2. Configure optional parameters
3. Run the actor and collect the results

### 💪 Limitations

- Respects Funda.nl's or Fundainbusiness.nl's terms of service
- Rate limiting applied to prevent blocking
- Maximum of 10000 results per search URL

#### Input Example 1

A full explanation of an input example in JSON.

```json
	{
        "searchUrls": ["https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"],
        "maxItems": 30,
        "proxyConfiguration": {
            "useApifyProxy": false,
            "apifyProxyGroups": [
                "RESIDENTIAL"
            ]
        }
    }
```

#### Output sample 1

The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

```json
[
	{
		"highlight": {},
		"agent": [
			{
				"logo_type": "new",
				"relative_url": "/makelaar/13026-smedema-makelaars-en-taxateurs/",
				"is_primary": true,
				"logo_id": 141935042,
				"name": "Smedema Makelaars & Taxateurs",
				"association": "NVM",
				"id": 13026
			}
		],
		"number_of_bedrooms": 3,
		"address": {
			"country": "NL",
			"province": "Limburg",
			"wijk": "Nieuw-Bergen",
			"city": "Bergen (LI)",
			"neighbourhood": "Nieuw-Bergen Kern",
			"identifiers": [
				"nl",
				"bergen-li/straat-siebengewaldseweg",
				"bergen-li",
				"gemeente-bergen-li",
				"provincie-limburg",
				"bergen-li/nieuw-bergen-kern",
				"bergen-li/wijk-nieuw-bergen",
				"5854pc",
				"5854",
				"regio-noord-limburg"
			],
			"municipality": "Bergen (LI)",
			"is_bag_address": true,
			"house_number": "38",
			"postal_code": "5854PC",
			"street_name": "Siebengewaldseweg"
		},
		"plot_area_range": {
			"gte": 456,
			"lte": 456
		},
		"blikvanger": {
			"enabled": false
		},
		"object_type": "house",
		"energy_label": "A",
		"floor_area": [
			125
		],
		"floor_area_range": {
			"gte": 125,
			"lte": 125
		},
		"type": "single",
		"thumbnail_id": [
			199527498,
			199527499,
			199527500,
			199527501,
			199527503,
			199527505,
			199527509,
			199527512,
			199527514,
			199527517,
			199527520,
			199527524,
			199527527,
			199527530,
			199527533,
			199527536,
			199527538,
			199527541,
			199527542,
			199527543,
			199527546,
			199527547,
			199527548,
			199527549,
			199527550,
			199527553,
			199527556,
			199527559,
			199527562,
			199527567,
			199527569,
			199527572,
			199527575,
			199527581,
			199527584,
			199527586,
			199527588,
			199527589,
			199527590,
			199527592,
			199527594,
			199527597,
			199527600,
			199527605,
			199527602,
			199527631
		],
		"offering_type": [
			"buy"
		],
		"price": {
			"selling_price": [
				499000
			],
			"selling_price_range": {
				"gte": 499000,
				"lte": 499000
			},
			"selling_price_type": "regular",
			"selling_price_condition": "kosten_koper"
		},
		"plot_area": [
			456
		],
		"id": 7332972,
		"available_media_types": [
			"floor_plan",
			"photo_360",
			"video"
		],
		"publish_date": "2024-10-25T15:15:02.5130000",
		"object_detail_page_relative_url": "/detail/koop/bergen-li/huis-siebengewaldseweg-38/43787335/",
		"status": "none",
		"number_of_rooms": 7,
		"_index": "listings-wonen-searcher-alias-prod",
		"_id": "7332972",
		"_score": null,
		"sort": [
			"basis",
			59000,
			7332972
		],
		"_click_id": 0,
		"placement": "listing_results_normal",
		"globalId": 7332972
	},
    ...
]
```

#### Input Example 2

A full explanation of an input example in JSON.

```json
	{
        "searchUrls": ["https://www.fundainbusiness.nl/alle-bedrijfsaanbod/heel-nederland/"],
        "maxItems": 30,
        "proxyConfiguration": {
            "useApifyProxy": false,
            "apifyProxyGroups": [
                "RESIDENTIAL"
            ]
        }
    }
```

#### Output sample 2

The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

```json
[
	{
		"title": "Lilienthalplein 1, Stadskanaal",
		"listing_url": "https://www.fundainbusiness.nl/kantoor/stadskanaal/object-43067560-lilienthalplein-1/?navigateSource=resultlist",
		"price": [
			"€ 319.000 k.k.",
			"€ 138 /m²/jaar"
		],
		"area": [
			"226 m²"
		],
		"image_url": "https://cloud.funda.nl/valentina_media/212/123/903_720x480.jpg",
		"image_alt": "Lilienthalplein 1, Stadskanaal",
		"makelaar": "Van Beilen Makelaars",
		"makelaar_url": "https://www.fundainbusiness.nl/makelaar/9216-van-beilen-makelaars/",
		"listing_type": "regular",
		"scraped_at": "2025-06-19T03:10:30.864Z"
	},
    ...
]
```

# Actor input Schema

## `searchUrls` (type: `array`):

List of Funda.nl search result URLs to scrape

## `maxItems` (type: `integer`):

Maximum number of items to scrape

## `proxyConfiguration` (type: `object`):

Proxy settings for the crawler

## Actor input object example

```json
{
  "searchUrls": [
    "https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"
  ],
  "maxItems": 30,
  "proxyConfiguration": {
    "useApifyProxy": false,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# 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 = {
    "searchUrls": [
        "https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"
    ],
    "maxItems": 30
};

// Run the Actor and wait for it to finish
const run = await client.actor("easyapi/funda-nl-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 = {
    "searchUrls": ["https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"],
    "maxItems": 30,
}

# Run the Actor and wait for it to finish
run = client.actor("easyapi/funda-nl-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 '{
  "searchUrls": [
    "https://www.funda.nl/en/zoeken/koop?selected_area=%5B%22bergen-li%22%5D&search_result=1"
  ],
  "maxItems": 30
}' |
apify call easyapi/funda-nl-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,easyapi/funda-nl-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/69aVxdpQm6bIIJyNb/builds/eySmaTtCv2bChugWj/openapi.json