Finn.no Scraper — Norwegian Property Listings | $1.50/1K | No Proxy

For Norwegian real estate investors, buyer's agents, and Nordic PropTech platforms who need structured data from Finn.no — Norway's dominant property portal with 95%+ market share.

$1.50 per 1,000 listings.

Scrape Finn.no — Norway's #1 classifieds and real estate portal. Extracts structured listing data from any search URL: price, total cost, shared expenses, address, area, ownership type, property type, bedrooms, viewing times, and photos.

No proxy required. No authentication. Parses HTML listing cards with parsel — stable field extraction.

What you get

Field	Description
listing_id	Finn code (finnkode)
title	Listing title
price	Asking price in NOK
price_raw	Raw price text
total_price	Total price including fees (NOK)
shared_expenses	Monthly shared expenses (NOK)
currency	Always "NOK"
area_m2	Living area in m²
ownership_type	"Selveier", "Aksje", "Andel", etc.
property_type	"Leilighet", "Enebolig", "Rekkehus", etc.
bedrooms	Number of bedrooms
address	Street address
city	City name
viewing	Next viewing date/time
url	Full Finn ad URL
image_url	Main listing photo (960px)
scraped_at	Scrape timestamp (ISO 8601 UTC)
parse_confidence	Data quality score 0.0–1.0
warnings	Quality issue codes

How it works

Finn.no renders listing cards server-side as <article> elements with full data in text content. The actor fetches search pages and parses each card using parsel CSS/text selectors. Pagination via ?page=N parameter.

~50 listings per page. No detail-page fetches needed.

Input

{
  "searchUrl": "https://www.finn.no/realestate/homes/search.html?location=0.20061",
  "maxItems": 50
}

Works with any Finn.no real estate search URL — location, price, size filters all work.

Output sample

{
  "listing_id": "382814524",
  "title": "Lys og pen 3-roms leilighet med balkong og garasjeplass",
  "price": 5490000,
  "total_price": 5742500,
  "shared_expenses": 4200,
  "currency": "NOK",
  "area_m2": 72,
  "ownership_type": "Aksje",
  "property_type": "Leilighet",
  "bedrooms": 2,
  "address": "Pilestredet 75C",
  "city": "Oslo",
  "viewing": "Lørdag 15. juni kl. 13:00",
  "url": "https://www.finn.no/realestate/homes/ad.html?finnkode=382814524",
  "parse_confidence": 0.95,
  "warnings": []
}

Pricing example

Run size	Cost
50 listings	~$0.075
1,000 listings	~$1.50
10,000 listings	~$15.00
+ viewing schedule	+$0.50/1K

FAQ

Do I need a Finn.no account or proxy? No account, no proxy. Works from Apify cloud IPs.

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

Are GPS coordinates included? Coordinates are not available from Finn.no search pages (search page only). Use the listing url to open the detail page for exact map location.

What if it returns empty results? Check that your searchUrl is a valid Finn.no real estate search URL (must include /realestate/). The actor logs the issue and exits cleanly with 0 results rather than crashing.

Why this actor vs. competitors

Feature	This actor	epctex/finn-scraper ($3/1K)	Typical Finn.no scraper
total_price (incl. fees)	Yes	No	Rarely
shared_expenses	Yes	No	No
ownership_type (Selveier/Aksje)	Yes	No	No
Viewing schedule	Yes	No	No
parse_confidence	Yes	No	No
Price per 1K listings	$1.50	$3.00	varies

Note: GPS coordinates not available in current version (search-page only). Use the listing URL for exact location.

Legal note: ownership_type (Selveier vs Aksje/Andel) is a legally critical field in Norway — cooperative (Aksje/Andel) ownership affects financing options. This field is unique to Norwegian real estate and rarely available in competing scrapers.

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/finn-listings"
}

Competitive edge

• parse_confidence + warnings on every record
• total_price + shared_expenses (full cost transparency)
• ownership_type (Selveier vs Aksje/Andel distinction)
• viewing date extracted
• No proxy COGS

Pricing

Pay-Per-Event (PPE):

Event	Price
listing-item (primary)	$1.50 / 1,000 listings
viewing-schedule (premium)	$0.50 / 1,000 listings with viewing dates

Listings with an upcoming viewing date fire the viewing-schedule event in addition to the base charge. Buyer's agents and buyer-coordination platforms use this field to track open-house schedules.

Integrations

Built for Norwegian real-estate investors and PropTech platforms monitoring Finn.no property prices and inventory — 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.