Kleinanzeigen Scraper - Germany Classifieds Data Extractor

🤖 What this actor does

The Kleinanzeigen Scraper extracts listing data from kleinanzeigen.de, one of Germany's largest classifieds marketplaces.

Kleinanzeigen includes many verticals like real estate, vehicles, electronics, home & garden, jobs, and more. This actor can search any category via a built-in category dropdown sourced from the live category tree.

It returns clean dataset items you can export as JSON, CSV or Excel.

💡 Typical use cases

• Monitor new listings for any niche or category
• Track prices over time in specific cities or ZIP codes
• Build lead lists from private or commercial sellers
• Collect listing data for market analysis and dashboards
• Fetch specific listings directly with adIds

🚀 How to use

1. Set maxItems.
2. Add a query (recommended).
3. Optionally choose category to target a specific category.
4. Add location filters (location, zipCode, coordinates, radius).
5. Run the actor and export your dataset.

If you set adIds, search is skipped and those listing IDs are fetched directly.

📝 Input parameters

Parameter	Type	Default	Description
maxItems	integer	50	Maximum number of listings to collect.
query	string		Search keywords, for example iphone, fahrrad, wohnung.
category	string (enum)	alle_kategorien	Category selector with all app categories. Values are mapped to numeric category IDs automatically.
location	string		City or region text, for example Berlin.
locationId	string		Advanced: Kleinanzeigen location ID if already known.
zipCode	string		Filter by ZIP code.
streetAddress	string		Filter by street/address text.
latitude / longitude	number		Coordinate-based search (use together).
distanceKm	integer	20	Search radius in kilometers.
minPrice / maxPrice	integer		Price range filter.
priceType	string		Advanced price type filter used by API.
adType	string (enum)		offered or wanted.
posterType	string (enum)		private or commercial.
sortType	string (enum)		Sorting option (recommended, newest, price, distance).
openHomesType	string (enum)		Open homes period: today, this_week, or this_weekend.
onlyWithPictures	boolean	false	Only listings with images.
excludeExternalListings	boolean	false	Exclude imported external listings.
includeTopAds	boolean	false	Include promoted top ads.
includeAdvertisingBackfillAds	boolean	false	Include ad backfill inventory.
updatedAfter	string (date)		Minimum updated date (YYYY-MM-DD).
updatedBefore	string (date)		Maximum updated date (YYYY-MM-DD).
sellerUserIds	array	[]	Advanced: only specific seller user IDs.
sellerStoreIds	array	[]	Advanced: only specific store IDs.
fetchDetails	boolean	false	Fetch full ad details for each listing (_details).
adIds	array	[]	Advanced direct mode. Numeric listing IDs only.

🔎 Example input (search mode)

{
  "maxItems": 100,
  "query": "iphone",
  "location": "Berlin",
  "distanceKm": 20,
  "minPrice": 100,
  "maxPrice": 800,
  "posterType": "private",
  "sortType": "newest",
  "onlyWithPictures": true,
  "updatedAfter": "2026-04-01",
  "fetchDetails": false
}

🗂️ Example input (search with category)

{
  "maxItems": 100,
  "query": "wohnung",
  "category": "immobilien_mietwohnungen",
  "location": "Berlin",
  "sortType": "newest"
}

🎯 Example input (direct IDs mode)

{
  "maxItems": 3,
  "adIds": ["3364756114", "3364700001", "3364609999"],
  "fetchDetails": true
}

📊 Output

Each dataset item is one listing. Common fields include:

• id
• title.value
• price.amount.value
• price.price-type.value
• poster-type.value
• category.id
• ad-address.zip-code.value
• ad-address.state.value
• store-title.value
• start-date-time.value
• _meta.url (listing URL)
• _meta.image (main image URL)

If fetchDetails is enabled, each item also includes _details with full listing payload.

⚠️ Notes

• fetchDetails adds extra requests per listing, so runs are slower and more expensive.
• Date filters accept YYYY-MM-DD and are normalized to day boundaries internally.