Fotocasa Property Listings Scraper

Use this Fotocasa API alternative to export public residential property listings from Fotocasa Spain into structured JSON, CSV, Excel, XML, or RSS. The Fotocasa scraper accepts search-result URLs to collect many homes or individual listing URLs for focused monitoring.

The Actor preserves Fotocasa data such as listing prices, descriptions, locations, coordinates, photos, property characteristics, and public advertiser details in one consistent dataset.

Quick start

Paste a public Fotocasa search or individual property URL, set maxListings to 10 and maxPages to 2, then start the Actor. Open the Dataset tab to inspect or download the saved listings. Availability of optional fields varies. Blocked or unexpected pages may fail a run.

{
  "startUrls": [{ "url": "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l" }],
  "maxListings": 10,
  "maxPages": 2
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

• Export Barcelona Fotocasa Rentals
• Export Madrid Fotocasa Homes for Sale

What you get

One row per unique saved public property listing, with available price, operation, location, characteristics, images and advertiser fields. Publication/update metadata and capture time support your own dated observations. Optional source values remain null, and change labels do not compare prior exports.

Who is it for?

This Actor is built for property analysts, real estate teams, investors, researchers and data engineers who need repeatable Fotocasa exports without manual copy-and-paste.

How you can use the data

• Prepare a Madrid sale-listing sheet. Use the existing Madrid search URL with small listing and page caps. Keep id, url, price, operation, area and collection time together before comparing source observations.
• Review a Barcelona rental sample. Use the existing rental example or your chosen public search URL. Inspect returned locations, features and source links without assuming complete city inventory or guaranteed current availability.
• Compare dated exports downstream. Match listing IDs or URLs in your own saved datasets and retain publishedAt and scrapedAt. changedSince classifies available source publication/update metadata but does not filter results, compare prices or identify newly seen inventory.
• Inspect selected known properties. Supply direct property URLs and an explicit listing cap. Each direct URL uses one page, and the compatibility detail switch does not add requests or exported fields.

Input settings

{
  "startUrls": [
    { "url": "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l" }
  ],
  "maxListings": 100,
  "maxPages": 5,
  "changedSince": "2026-08-01T00:00:00Z"
}

More input settings

Field	Type	Description
startUrls	array	One or more public Fotocasa search-result or individual property URLs.
maxListings	integer	Global maximum number of unique listings to export.
maxPages	integer	Maximum result pages visited for each search URL. Individual property URLs use one page.
includeDetails	boolean	Accepted compatibility setting. Does not enable extra requests or change exported fields.
changedSince	ISO date/time	Labels rows using available publication/update dates. Does not filter results or detect price changes.

Collect Madrid homes for sale

Use a Fotocasa Madrid sale-results URL with maxListings: 100 and maxPages: 5.

Monitor rental inventory

Use a rental search URL and schedule collection externally. You can set changedSince to your prior collection timestamp for source-date labels, but compare saved exports yourself to detect newly seen listings or price changes.

Export selected properties

Pass multiple individual listing URLs in startUrls and set maxListings to the number of URLs.

Output data

Illustrative shape only, not a captured listing. Optional values depend on what the source exposes.

{
  "id": "190235067",
  "url": "https://www.fotocasa.es/es/comprar/vivienda/madrid-capital/example/190235067/d",
  "title": "Flat in Madrid",
  "description": "Bright home with parking and storage.",
  "operation": "sale",
  "propertyType": "Flat",
  "price": 390000,
  "pricePerSquareMeter": 4875,
  "area": 80,
  "rooms": 2,
  "bathrooms": 1,
  "floor": "3",
  "address": "Madrid, 28022",
  "location": "Madrid",
  "latitude": 40.4241,
  "longitude": -3.6014,
  "features": ["Parking", "Lift"],
  "images": ["https://static.fotocasa.es/images/ads/example"],
  "imageCount": 1,
  "agencyName": null,
  "agencyPhone": null,
  "energyRating": "C",
  "publishedAt": "2026-08-06T10:00:00Z",
  "sourceUrl": "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l",
  "pageNumber": 1,
  "scrapedAt": "2026-08-06T12:00:00Z",
  "changeStatus": "new"
}

Fields that Fotocasa does not expose for a particular listing are returned as null. Arrays remain arrays.

More output fields

Field	Description
id	Fotocasa listing identifier.
url	Canonical public property URL.
title	Listing headline.
description	Public listing description.
operation	Sale or rent operation.
propertyType	Property type or subtype.
price	Advertised price in euros.
pricePerSquareMeter	Advertised or available price per square metre.
area	Property area when available.
rooms	Number of rooms or bedrooms.
bathrooms	Number of bathrooms.
floor	Floor label.
address	Public address or area label.
location	Municipality, district, neighborhood, or location label.
latitude, longitude	Public listing coordinates.
features	Public property features and amenities.
images	Public image URLs.
imageCount	Number of images.
agencyName	Public advertiser or agency name.
agencyPhone	Public advertiser phone number.
energyRating	Energy rating when available.
publishedAt	Publication or update timestamp when available.
sourceUrl	Input or pagination URL that produced the row.
pageNumber	Search page number.
scrapedAt	UTC extraction timestamp.
changeStatus	new when available publication/update metadata is at or after changedSince. Otherwise current. Not a comparison with prior runs.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

Pay-per-event pricing uses one start event per run and one result event per saved listing. A started run can incur the start fee even when no listings are exported. Collection stops when the next event no longer fits the run's budget. Output is saved before billing; RUN_SUMMARY reports saved and actually charged result counts separately. Error or status rows are not saved or charged as listings.

Use listing and page caps to bound collection, without treating them as a fixed spend guarantee. See the live Pricing tab for current rates and plan discounts.

Tips for best results

• Start with a focused public search and small caps. Inspect output before expanding the number of pages or listings.
• Use canonical public search or property URLs. Keep source links with each row for later review.
• Compare source dates with capture time deliberately. A new change label is based on metadata, not remembered results from a prior run.
• Inspect missing optional fields before analysis. Values and available public advertiser details can differ by property.
• Choose your own downstream comparison step. A schedule collects again but does not automatically calculate price changes.

Limits and caveats

Results reflect public page data available during the run. Removed or unavailable listings cannot be exported, optional values can be null and coverage is not guaranteed complete inventory. Rows follow source discovery order without a separate sorting control.

No matches, unavailable targets (HTTP 404/410) and completed extraction with zero usable priced records finish successfully without placeholder rows. RUN_SUMMARY in the run's key-value store records each visited page's reason and saved count. An unexplained zero-record extraction also emits a separate parser diagnostic; empty success does not prove a listing was deleted, private or that extraction is working correctly. Blocking, upstream errors, network failures, billing errors and essential storage failures still fail the run. Previously saved rows remain available.

Collection accepts at most 100 start URLs and makes at most 100 transport requests (including location lookups and fallback attempts), with no automatic retries and at most two redirects per request. Processing stops within a 240-second application budget (or earlier for the platform deadline, listing cap or billing capacity). Responses over 2 MiB fail safely. Supported Spanish and English residential searches and property details use Fotocasa's anonymous public JSON gateway without a proxy, retaining the selected language and sale/rental operation. This includes the constructionTypeIds URL filter: 1 selects new construction, 2 selects second-hand homes, and 1,2 selects both. Supported semicolon-separated otherIds selections for bank-owned homes, photos, videos, completed properties, building specifications, tours, price drops and subsidized housing also retain their filters on the gateway. Quality-seal (10) and Catalyst (50) contract selections use the current public search API, including combinations with other supported filters. Unknown, malformed or conflicting selections retain the HTML route. Other URL shapes or unsupported query parameters retain the existing Spanish residential HTML route; an unavailable gateway may also fall back to that route. Your target and filters are never silently discarded. RUN_SUMMARY separates gateway and residential request counts. A detail payload without a usable price returns no row with reason no_usable_price; ordinary expected emptiness does not emit a parser incident. RUN_SUMMARY reports the stop reason; a bounded partial run is not a claim of complete inventory. Restarting a previously start-charged run is rejected to avoid repeated extraction; start a new run instead.

The includeDetails compatibility setting does not fetch additional pages or change exported fields. Only data present in fetched pages is available. Individual property URLs use one page, while page limits apply per search URL and the unique-listing cap applies across the run.

The changedSince value labels a row new when available publication/update metadata is at or after the supplied date, otherwise current. It does not filter exports or compare with prior runs, and it does not detect price changes or newly seen inventory. Keep source timestamps and collection time separate in your own analysis.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~fotocasa-property-listings-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "startUrls": [
    {
      "url": "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l"
    }
  ],
  "maxListings": 10,
  "maxPages": 2
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/fotocasa-property-listings-scraper').call({
  "startUrls": [
    {
      "url": "https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l"
    }
  ],
  "maxListings": 10,
  "maxPages": 2
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/fotocasa-property-listings-scraper').call(run_input={'startUrls': [{'url': 'https://www.fotocasa.es/es/comprar/viviendas/madrid-capital/todas-las-zonas/l'}], 'maxListings': 10, 'maxPages': 2})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents

You can ask your AI assistant to collect data with Fotocasa Property Listings Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Fotocasa Property Listings Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/fotocasa-property-listings-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Fotocasa Property Listings Scraper by Fetch Cat, or give it the identifier fetch_cat/fotocasa-property-listings-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s Fotocasa Property Listings Scraper to collect up to 5 Madrid homes for sale from the existing public search URL, with at most 1 result page. Show listing links, advertised euro prices, area and available room counts.”
• “Collect at most 5 properties from the Barcelona rental search URL I provide, using one result page. Keep listing IDs, operation, source dates and collection times for my own saved-export comparison.”
• “Retrieve up to 2 properties from the direct Fotocasa URLs I supply. Show available location, features and public advertiser fields, marking missing values without claiming complete inventory or built-in change detection.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

How can I export Fotocasa listings?

Supply a public search URL, choose a result limit, and download the resulting dataset in JSON, CSV, Excel, XML, or RSS.

Is there a Fotocasa API for property data?

This Actor provides an API-accessible workflow for public Fotocasa property data through Apify clients, REST endpoints, schedules, integrations, and MCP.

How can I monitor Fotocasa prices?

Compare saved datasets from repeat runs using listing id and price. The Actor does not store a price history or calculate price changes. changeStatus only classifies available publication/update dates against your timestamp.

Can I scrape rental and sale listings?

Yes. Supply the corresponding public Fotocasa search or listing URL.

Does it paginate search results?

Yes. maxPages bounds pages per search, while maxListings caps the total unique rows.

Can I run it on a schedule?

Yes. Create an Apify schedule and use changedSince to classify recently published listings when the source provides publication metadata.

Can I use the results through an API or MCP?

Yes. Every run can be started through the Apify API, JavaScript/Python clients, webhooks, integrations, or Apify MCP.

Why are some fields null?

Fotocasa does not expose every attribute for every property. The Actor preserves truthful source availability instead of inventing values.

Is this an official Fotocasa product?

No. This independent Actor extracts information available on public pages.

Related Actors

• Idealista Market Intel Scraper — Spanish property research.
• Zillow Property Listings Scraper — US listing searches.
• Zillow Property Details Scraper — Individual US properties.
• Rightmove Property Listings Scraper — UK listing research.
• Redfin Property Listings Scraper — Additional US property data.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥