CommercialGuru Singapore Scraper

Extract commercial property listings from commercialguru.com.sg (PropertyGuru Group) at scale. Get comprehensive data including prices, PSF, floor area, tenure, images, agent contacts, coordinates, nearby MRT, and more. Perfect for Singapore commercial property analytics, investment research, and market intelligence.

Key Features

Feature	Description
All Listing Types	For Sale and For Rent commercial properties across Singapore
11 Property Types	Office, Retail, Shop/Shophouse, Warehouse, Factory, Industrial, Land, F&B, Business Park, Dormitory
Price & Size Filters	Narrow results by price range (SGD) and floor area (sqft)
Location Filters	Filter by district (D01-D28) or freetext search
Exact Coordinates	Lat/lng enrichment via PropertyGuru Map Cluster API
Multiple Dataset Views	Overview, Map View, Agents & Developers
Pagination	Multi-page scraping with automatic retry on blocked pages

What data can you extract?

The scraper extracts 25+ fields per listing:

Property Details Listing ID & URL Title & full address Property type (Office, Retail, Shophouse, etc.) Floor area & land area (sqft) Tenure (Freehold/Leasehold) Badges (unit type, tenure, year built, etc.)	Pricing Price (SGD numeric value) Formatted price (e.g. "S$ 3,800,000") Price per sqft (PSF) Listing type (Sale/Rent)
Location & Transit Latitude & longitude (from Map Cluster API) District name & code (D01-D28) Region grouping Nearest MRT station with distance	Agent & Developer Agent name, ID & CEA license Agency name Developer name Is developer listing flag
Media Property images (up to 10 per listing) Image count	Dates & Metadata Posted date (text & unix timestamp) Recency text Listing status (Active, etc.)

With fetch_details enabled, each listing also includes:

Description & Terms Full description & headline Lease term (e.g. "2 years") Rental type (e.g. Entire Unit) Condition (e.g. Fully Fitted) Unit features & amenities Floor level Available-from date

Location & Contact Exact coordinates (from the listing page) Postal code Agent phone (mobile) & title Nearby MRT stations (with distance & walk time) Nearby schools Full image gallery (beyond the 10-image card cap)

Coordinates are also added by the separate enable_coordinates option (via the Map API). fetch_details is slower and uses more proxy traffic; both are off by default.

Incremental mode only. When incrementalMode is on, every returned record also carries:

Field	Description
changeType	NEW | UPDATED | UNCHANGED | REAPPEARED | EXPIRED
changedFields	Top-level fields that changed since last seen; non-empty only for UPDATED
firstSeenAt	When this listing was first observed by this monitoring campaign
lastSeenAt	When this listing was last observed

How to Use

Step 1: Search offices for rent in CBD

{
  "mode": "search",
  "listing_type": "rent",
  "property_type": "office",
  "search": "Raffles Place",
  "max_properties": 50,
  "max_pages": 5
}

Step 2: Filter shops by district and price

{
  "mode": "search",
  "listing_type": "sale",
  "property_type": "shop",
  "district": "D01",
  "min_price": 500000,
  "max_price": 5000000,
  "max_properties": 100,
  "max_pages": 10
}

Step 3: Warehouses by floor area

{
  "mode": "search",
  "listing_type": "rent",
  "property_type": "warehouse",
  "min_floor_area": 5000,
  "max_floor_area": 20000,
  "sort": "price",
  "sort_order": "asc"
}

Step 4: Scrape specific URLs

{
  "mode": "url",
  "urls": [
    "https://www.commercialguru.com.sg/office-for-rent?district_code=D01",
    "https://www.commercialguru.com.sg/shop-for-sale?freetext=Orchard"
  ],
  "max_properties": 50,
  "max_pages": 5
}

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search (build URL from filters) or url (use provided URLs)
urls	array	[]	CommercialGuru search URLs (url mode only)
listing_type	string	sale	sale or rent
property_type	string	-	See Property Types table below
locations	array	[]	One or more locations to search (e.g. ["Raffles Place", "Jurong"]). Each is searched separately and results are combined. Takes priority over search.
search	string	-	Single free-text location search (e.g. "Raffles Place", "Jurong", "CBD")
district	string	-	District code D01-D28 (see table below)
min_price	integer	-	Minimum price in SGD
max_price	integer	-	Maximum price in SGD
min_floor_area	integer	-	Minimum floor area in sqft
max_floor_area	integer	-	Maximum floor area in sqft
sort	string	date	Sort by: date, price, psf, area (floor area)
sort_order	string	desc	asc or desc
max_properties	integer	10	Max listings to scrape (0 = unlimited)
max_pages	integer	5	Max search result pages (20 listings/page)
enable_coordinates	boolean	false	Add lat/lng to listings via Map API. Slows down the run (~30-60s extra).
fetch_details	boolean	false	Adds extra fields per listing: full description, agent phone, exact coordinates, postal code, full image gallery, nearby MRT & schools, lease term, condition, amenities, and floor level. Slower and uses more proxy traffic.
resumeFromRunId	string	none	Continue one specific previous run/dataset: properties already collected there are skipped. For recurring monitoring, use Incremental mode instead — see "Resume & recurring updates" below.
incrementalMode	boolean	false	Daily/recurring monitoring of this same search. First run returns everything as NEW; later runs return only NEW/UPDATED/REAPPEARED by default. See "Resume & recurring updates" below.
stateKey	string	none	Incremental mode only. Name this monitoring campaign, or leave empty to derive one automatically from the search/filter settings.
emitUnchanged	boolean	false	Incremental mode only. Also return properties unchanged since the last run, marked UNCHANGED. Adds and bills extra rows you already have.
emitExpired	boolean	false	Incremental mode only. Also return properties from a previous run no longer found, marked EXPIRED, once a run has fully scanned the search (not capped, not a resume). Adds and bills extra synthetic rows.
proxy	object	Apify residential	Proxy configuration (Apify proxy recommended)
dataset_name	string	default	Named dataset for results
clear_dataset	boolean	false	Clear dataset before scraping

Property Types

Code	Type	Description
office	Office	Office spaces
retail	All Retail	All retail properties (shops, F&B, etc.)
shop	Shop / Shophouse	Shops and shophouses
shophouse	Shophouse	Shophouses specifically
warehouse	Warehouse	Warehouse spaces
factory	Factory / Industrial	All factory and industrial properties
industrial	All Industrial	All industrial types (factory, warehouse, dormitory)
land	Commercial Land	Commercial land plots
food_beverage	Food & Beverage	F&B outlets and restaurants
business_park	Business / Science Park	Business and science park spaces
dormitory	Dormitory	Worker dormitories

Singapore Districts

Code	Area	Code	Area
D01	Raffles Place / Marina	D15	East Coast / Marine Parade
D02	Chinatown / Tanjong Pagar	D16	Bedok / Upper East Coast
D03	Alexandra / Commonwealth	D17	Changi Airport / Changi Village
D04	Harbourfront / Telok Blangah	D18	Pasir Ris / Tampines
D05	Buona Vista / West Coast	D19	Hougang / Punggol / Sengkang
D06	City Hall / Clarke Quay	D20	Ang Mo Kio / Bishan / Thomson
D07	Beach Road / Bugis	D21	Clementi Park / Upper Bukit Timah
D08	Farrer Park / Serangoon Rd	D22	Boon Lay / Jurong / Tuas
D09	Orchard / River Valley	D23	Bukit Batok / Bukit Panjang
D10	Tanglin / Holland / Bukit Timah	D24	Lim Chu Kang / Tengah
D11	Newton / Novena	D25	Admiralty / Woodlands
D12	Balestier / Toa Payoh	D26	Mandai / Upper Thomson
D13	Macpherson / Potong Pasir	D27	Sembawang / Yishun
D14	Eunos / Geylang / Paya Lebar	D28	Seletar / Yio Chu Kang

Resume & recurring updates

There are two different things here — pick the one that matches what you're doing:

Need	Use
A crawl stopped and should continue	resumeFromRunId
Run the same search every day and receive only changes	incrementalMode
Keep separate daily campaigns for similar searches	distinct stateKey values
Run a normal full snapshot	leave both off

Resume (resumeFromRunId) continues one specific interrupted or previous large crawl: paste a run ID or dataset ID and this run skips properties already collected there, returning only the remaining new ones.

Incremental mode (incrementalMode) is for a schedule (for example, daily): the actor remembers the previous run of the same search by itself, so you never paste a run ID. The first run returns everything as NEW. Later runs return only NEW, UPDATED, and REAPPEARED properties by default — duplicates and unchanged properties are suppressed (never pushed, never billed). Turn on emitUnchanged or emitExpired only when you also want those rows returned (and billed for). State is isolated per search/URL and filter/fetch_details/enable_coordinates setup automatically; set stateKey to name or deliberately share a monitoring campaign.

Identity is tracked by id — commercialguru.com.sg's own listing id (every parsed listing has one; a listing without an id is dropped before it reaches change detection). One field is excluded from change detection: recency (e.g. "Listed on Aug 03, 2026 (2h ago)") is a relative-age string the site renders at request time, so it drifts with elapsed time alone, not real content — it is still returned in full on every row, just never used to decide UPDATED. posted_date/posted_unix (the real "when was this posted" fields) stay in change detection.

If fetch_details is on and a listing's own detail-page fetch fails on a given run (a transient block, not every listing on the page), that listing's detail-only fields are treated as unknown for this run, not removed — the actor carries the last successful detail snapshot forward before comparing, so a transient per-listing failure is reported UNCHANGED and never bills, and recovers cleanly once the fetch succeeds again. A genuine change to any field the fetch DID return (including price) is still reported normally.

Scheduled-run example — same search, run daily:

Day 1 (first run ever for this search):

{ "mode": "search", "listing_type": "sale", "district": "D01", "incrementalMode": true }

→ every listing comes back with "changeType": "NEW".

Day 2 (the schedule fires again, identical input):

{ "mode": "search", "listing_type": "sale", "district": "D01", "incrementalMode": true }

→ listings whose price/tenure/etc. changed come back as "changeType": "UPDATED" with changedFields listing what changed, brand-new listings come back as "changeType": "NEW", listings that vanished and came back come back as "changeType": "REAPPEARED" — and listings that are still there, unchanged, are not returned at all (suppressed, not charged) unless emitUnchanged is on. EXPIRED tombstones for listings no longer found are only produced when emitExpired is on and the run fully scanned the tracked search (not capped by Max properties, not a resume).

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape — the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record — not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify → Settings → Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Output Example

Commercial property listing

{
  "id": 500073292,
  "title": "Novena Medical Center",
  "address": "10 Sample Drive",
  "listing_type": "sale",
  "property_type": "Office",
  "property_type_group": "O",
  "price": 3800000,
  "price_formatted": "S$ 3,800,000",
  "currency": "SGD",
  "price_psf": "S$ 4,973.82 psf",
  "floor_area": 764,
  "tenure": "99-year Leasehold",
  "agent_name": "Sample",
  "agent_id": 1758000,
  "agent_license": "R0123000",
  "agency_name": "Sample PTE LTD",
  "district": "Newton / Novena",
  "district_code": "D11",
  "region": "Central (D09-11)",
  "nearby_mrt": "2 min (170 m) from NS20 Novena MRT Station",
  "latitude": 1.3000,
  "longitude": 103.000,
  "location_source": "map_api",
  "badges": ["Office", "99-year Leasehold"],
  "posted_date": "2 Apr 2026",
  "posted_unix": 177508000,
  "recency": "Listed on Apr 02, 2026 (30m ago)",
  "images": [
    "https://sg1-cdn.pgimgs.com/listing/500073292/UPHO.123456.V800/Novena-Sample.jpg"
  ],
  "image_count": 1,
  "url": "https://www.commercialguru.com.sg/listing/for-sale-novena-medical-center-Sample",
  "status": "ACT"
}

Additional fields with fetch_details enabled

{
  "description": "Rare freehold ground-floor medical suite.\nFully fitted, ready to move in.\nHigh footfall, wide frontage.",
  "description_headline": "Freehold medical suite, fully fitted",
  "postal_code": "307506",
  "latitude": 1.3201,
  "longitude": 103.8439,
  "location_source": "detail_page",
  "agent_phone": "+6580001234",
  "agent_title": "Associate Group Director",
  "floor_level": "Ground Floor",
  "rental_type": "Entire Unit",
  "unit_condition": "Fully Fitted",
  "unit_features": ["Air Conditioner"],
  "lease_term": "99 years",
  "amenities": ["Air conditioner"],
  "nearby_mrt_stations": [
    { "name": "NS20 Novena MRT Station", "distance_km": 0.17, "walk_minutes": 2 }
  ],
  "nearby_schools": [
    { "name": "Sample Primary School", "distance_km": 0.45, "walk_minutes": 6 }
  ],
  "available_date": "2026-06-15 00:00:00",
  "detail_fetched": true
}