Immobiliare.it Scraper — Italian Real Estate | $1.50/1K | No Proxy

For Italian property investors, international real estate funds, and PropTech platforms targeting Italy's 1.3M annual transactions market — the largest in Southern Europe.

$1.50 per 1,000 listings. Luxury and new-construction listings available as premium events.

Scrape Immobiliare.it — Italy's #1 real estate portal. Extracts structured listing data from any search URL: price, address, city, rooms, surface area, floor, GPS coordinates, and photos.

No proxy required. No authentication. Parses embedded __NEXT_DATA__ JSON — stable and fast.

What you get

Field	Description
listing_id	Immobiliare numeric listing ID
uuid	Listing UUID
title	Listing title
description	Full description text
price	Price in EUR (int)
price_formatted	Formatted price string (e.g. "€ 319,000")
contract	"sale" or "rent"
property_type	Type (e.g. "Apartment", "Villa")
address	Street address
city	City name
province	Province
region	Region (e.g. "Lazio")
macrozone	Neighborhood zone
microzone	Sub-neighborhood
lat, lng	GPS coordinates
surface_m2	Living area in m²
rooms	Total rooms
bathrooms	Bathrooms
bedrooms	Bedrooms
floor	Floor description
energy_class	EU energy class (A–G)
is_new	New construction flag
is_luxury	Luxury listing flag
has_elevator	Elevator present
url	Full listing URL
image_url	Main photo URL
images	All photo URLs
scraped_at	Scrape timestamp (ISO 8601 UTC)
parse_confidence	Data quality score 0.0–1.0
warnings	Quality issue codes

How it works

Immobiliare.it uses Next.js SSR. All listing data is embedded in __NEXT_DATA__ → dehydratedState.queries[0].state.data.results — no DOM parsing, no fragile CSS selectors. Pagination via ?pag=N.

Input

{
  "searchUrl": "https://www.immobiliare.it/en/vendita-case/roma/",
  "maxItems": 50
}

Works with any Immobiliare.it search URL — sale/rent, city, neighborhood filters all work.

Output sample

{
  "listing_id": 99812345,
  "title": "Appartamento in vendita, Via del Corso, Roma",
  "price": 319000,
  "price_formatted": "€ 319,000",
  "contract": "sale",
  "property_type": "Apartment",
  "city": "Roma",
  "province": "RM",
  "macrozone": "Centro Storico",
  "surface_m2": 76,
  "rooms": 3,
  "bathrooms": 1,
  "is_new": false,
  "is_luxury": false,
  "lat": 41.8967,
  "lng": 12.4822,
  "url": "https://www.immobiliare.it/en/annunci/99812345/",
  "parse_confidence": 1.0,
  "warnings": []
}

Pricing example

Run size	Cost
50 listings	~$0.075
1,000 listings	~$1.50
10,000 listings	~$15.00
+ luxury listing	+$2.00/1K
+ new-construction	+$1.00/1K

FAQ

Do I need an Immobiliare account or proxy? No account, no proxy. Works from Apify cloud IPs with both /en/ (English) and Italian-language URLs.

What output formats are available? JSON, CSV, Excel, XML — all via Apify dataset download or API.

Can I filter for only rental listings? Paste any Immobiliare.it URL — both sale (/vendita-case/) and rental (/affitti-case/) URLs work.

What if it returns empty results? Check that your searchUrl is a valid Immobiliare.it search URL. The actor logs the issue and exits cleanly with 0 results rather than crashing.

Why this actor vs. competitors

Feature	This actor	epctex/immobiliare-scraper ($3/1K)	Typical Immobiliare scraper
Luxury flag (is_luxury)	Yes	No	No
New construction flag (is_new)	Yes	No	No
Macrozone + microzone	Yes	No	Rarely
parse_confidence + warnings	Yes	No	No
Floor field	Yes	Rarely	Rarely
Source: __NEXT_DATA__ JSON	Yes (stable)	DOM	DOM
Price per 1K listings	$1.50	$3.00	varies

Works with both English (/en/) and Italian Immobiliare.it URLs.

Unique fields: is_luxury and is_new flags make this actor ideal for luxury real estate agencies and property developer pipelines. macrozone + microzone provide sub-neighborhood granularity not available in any other Italian real estate actor.

parse_confidence

Every listing includes a parse_confidence score (0–1). Score < 0.8 means one or more critical fields are missing — check the warnings array before relying on those records.

Use with AI agents (MCP)

Tag: MCP_SERVERS. Returns clean JSON — drop into any n8n / Make / LangChain workflow without post-processing.

{
  "mcpServer": "https://mcp.apify.com/?tools=bovi/immobiliare-listings"
}

Competitive edge

• Parses embedded JSON state, not DOM — survives redesigns
• parse_confidence + warnings on every record
• GPS coordinates, macrozone, microzone included
• is_luxury and is_new flags — unique in the Italian real estate scraper space
• No proxy COGS

Pricing

Pay-Per-Event (PPE):

Event	Price
listing-item (primary)	$1.50 / 1,000 listings
luxury-listing (premium)	$2.00 / 1,000 luxury listings
new-construction (premium)	$1.00 / 1,000 new-build listings

Luxury (is_luxury=true) and new-construction (is_new=true) listings each fire their respective premium event in addition to the base charge. Filter for luxury or new-build buyers by checking these flags in the output.

Integrations

Built for Italian property investors, PropTech platforms, and real-estate funds tracking listings, prices, and GPS data — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.