HouseSigma Scraper: Canadian Property Listings, Sold History and Agents

HouseSigma Scraper turns HouseSigma into structured Canadian real estate data. Search Ontario, British Columbia and Alberta by city with full filters, or paste listing and area links, and get clean records: addresses, prices, every photo, room dimensions, school scores, price history, the HouseSigma price estimate and community sold statistics. Five modes cover filtered search, direct links, listing IDs, the agent directory and community sold-price stats. Export to JSON, CSV or Excel, or pull results straight into your app through the API. No login or cookies required.

Why This Scraper?

• No login or cookies required. The actor mints its own anonymous session and runs out of the box, with nothing to copy from your own account first.
• Five modes, not one. Search by filters, scrape pasted links, fetch listing details by ID, browse the agent directory, or pull community sold-price statistics, all from one actor.
• Rich detail per property. Turn on full details and get every photo, the virtual tour link, all rooms with dimensions, key facts, property features, full price history, nearby school scores, the HouseSigma price estimate and community sold trends.
• Filters applied at the source. Status, property type, price, bedrooms, bathrooms, garage spaces, size, listing age, assignment or resale, community and sort order all narrow the search before a single result page is fetched.
• Stable, structured output. Every listing comes back as the same flat field set, so a layout change on the site does not reshape your data.
• Built for recurring monitoring. Incremental mode tracks one search across scheduled runs and returns only what is new or changed, and a separate resume option continues one interrupted run without re-scraping what it already saved.
• Optional export to the apps you use. Pipe results into Notion, Linear or Airtable through MCP connectors, on top of the regular dataset.

Use Cases

• Home buyers and agents: track new listings and price changes across specific cities or filters as soon as they appear.
• Market research and appraisal: pull recent sold prices, days on market and community statistics to price a property or a neighborhood.
• Real estate investors: screen large areas for detached homes, condos or land in a price and size range, then rank by price or recency.
• Lead generation: build a directory of agents by city with their listing volume, property-type mix and active inventory.
• Data teams and dashboards: schedule recurring pulls of the same search and receive only new, updated or expired listings on each run.

Data You Get

Sample shape: values are illustrative placeholders, not from a live listing.

Field	Example
idListing	"00000000000000AB"
url	"https://housesigma.com/on/toronto-real-estate/1-sample-st/home/00000000000000AB/"
status	"For Sale"
saleOrLease	"Sale"
propertyType	"Detached"
address	"1 Sample Street"
municipality / community	"Toronto" / "Sample Community"
province	"Ontario"
bedrooms / bathrooms	3 / 2
priceListed / priceListedText	1200000 / "1,200,000"
priceSold	"(Sign-in required)": HouseSigma only shows sold prices to signed-in users, so anonymous runs return this placeholder
mlNum	null when the source masks it for anonymous sessions, otherwise the MLS number
latitude / longitude	43.6500 / -79.3800
sizeText	"1500 ft²"
dateListed / daysOnMarket	"2026-01-01" / 12
photos	["https://cache16.housesigma.com/file/pix/00000000/0000_1.jpg", "..."] (full details only)
virtualTour	link or null (full details only)
keyFacts	{ "Tax": "$0,000 / 2025", "Lot Size": "00 x 000 feet", "Parking": "2 garages" } (full details only)
rooms	[{ "type": "Living", "level": "Main", "dimensions": "0.00 x 0.00" }] (full details only)
schools	nearby school names and scores (full details only)
priceHistory	[{ "price": "1,200,000", "status": "For Sale", "date_start": "2026-01-01" }] (full details only)
estimate	{ "priceInt": 1180000, "confidence": 0.8, "rentInt": 3500 } (full details only)
communityStats	median sold price, average days on market and related trends for the area (full details only)

Full-detail and search records also carry extra flat fields: taxAnnual, maintenanceFee, crossStreet, openHouseDate, assessment, listingPriceChange, postalCode, brokerage, listAgentName, bedroomString, priceOrigin, priceTag, idCommunity, idMunicipality, dateStart, dateAddedDays and more. The Output tab has a view per record kind: Overview, Listing details, Agents, Agent listings, Community stats and Changes (incremental).

Note: HouseSigma only shows sold prices and the MLS numbers of sold and leased records to signed-in users. priceSold therefore comes back as "(Sign-in required)", and mlNum is null on sold and leased records. Every other field, including the full address, photos, rooms, price history and community trends, is returned in full.

Agent directory mode and agent-specific runs return agent records instead of listings: agentId, slug, name, avatar, title, brokerage, languages and a profile url, plus, when you name specific agents, a fuller profile with about text, career stats, top cities and property-type mix, and that agent's own listings tagged with agentSlug and a lightweight price estimate. Community mode returns one record per community with idCommunity, idMunicipality, community, municipality, province and nested detail / soldPriceStats objects covering median sold price, days on market and volume trends for that area.

How to Use

1. Pick a mode: search (filters), url (paste listing or area links), detail (listing IDs), agent (directory or named agents), or community (sold-price stats).
2. For search, set the province, cities or communities and filters. For url or detail, paste the links or IDs instead. Turn Fetch full details on for the complete photo, room, school and estimate payload, or off for a faster, lighter run of search-card fields only.
3. Set Max results (and optionally Max pages) to control run size and cost, then click Start.
4. Download the dataset as JSON, CSV or Excel, or read it through the API.

Search a city for properties on sale, with full details:

{
  "mode": "search",
  "province": "ON",
  "locations": ["Toronto"],
  "status": ["for-sale"],
  "fetchDetails": true,
  "maxItems": 50
}

Filtered search (3+ bedroom detached homes, 800k to 1.5M, cheapest first):

{
  "mode": "search",
  "locations": ["Mississauga", "Brampton"],
  "status": ["for-sale"],
  "propertyTypes": ["detached"],
  "minBedrooms": 3,
  "minPrice": 800000,
  "maxPrice": 1500000,
  "sortBy": "price-asc",
  "maxItems": 100
}

Scrape specific listing links:

{
  "mode": "url",
  "urls": ["https://housesigma.com/on/toronto-real-estate/1-sample-st/home/00000000000000AB/"]
}

Community sold-price statistics:

{
  "mode": "community",
  "province": "ON",
  "locations": ["Danforth"]
}

Supported URL shapes

url mode accepts these link types. If you leave urls untouched, url mode scrapes one example of each shape below. This is a change from earlier versions, where the default was a single sample listing, so trim the list to what you need.

Shape	Example	What you get
Listing detail page	https://housesigma.com/on/toronto-real-estate/410-90-niagara-street/home/aQmD7zn5m8Z7J9Bo/	One full listing record
City / area listings page	https://housesigma.com/on/toronto-real-estate/	Every listing in that city, paged
Province map page	https://housesigma.com/on/map/	Listings across the province (ON, BC, AB)
Other-province city page	https://housesigma.com/bc/vancouver-real-estate/	Listings for that city in its own province
Paginated area page	https://housesigma.com/on/toronto-real-estate/?page=2	The walk starts at that result page; an incremental run treats it as a partial scope and skips EXPIRED marking
Agent profile page	https://housesigma.com/on/agents/sneh-shekhada/	The agent profile plus that agent's listings
Legacy agents directory	https://housesigma.com/h5/en/agents	The agent directory

Any other link logs a warning (Unrecognized URL) and is skipped, and the run does not mark that scope as fully scanned. A city name in locations is resolved through the site's own search; if none of the names match, the run fails with a clear error.

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/housesigma-com").call(run_input={"mode": "search", "locations": ["Toronto"], "status": ["for-sale"]})
for listing in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(listing["address"], listing["priceListedText"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/housesigma-com').call({ mode: 'search', locations: ['Toronto'], status: ['for-sale'] });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

Max results, Max pages and long crawls

Leave Max pages empty to walk every result page for each location (a hard cap of 200 pages per location always applies); set it to cap how many pages (20 listings each) a single location can use. For an unbounded pull, a checkpoint survives a platform migration or a killed and resurrected run by remembering which records were already saved, and resumeFromRunId lets you continue the same catalogue walk in a brand-new run: paste a previous run or dataset ID and this run skips everything already collected there, appending only new records.

Resume and Incremental mode

resumeFromRunId and incrementalMode solve two different problems. Resume continues one specific interrupted run. Incremental mode is for scheduling this same search again and again (for example daily) and getting only what changed, without pasting any run or dataset ID.

Turn on incrementalMode and each run classifies every record against the state saved from the last run on the same search (kept internally, keyed by search mode, locations and filters, or by your own stateKey):

• NEW: not seen before.
• UPDATED: seen before, and at least one field changed (changedFields lists which).
• UNCHANGED: seen before, nothing changed. Suppressed (not returned or billed) unless emitUnchanged is on.
• EXPIRED: previously tracked, not found this run. Only produced when a run fully scans the tracked search, not capped by Max results, not cut short by Max pages, and not a resume, and only when emitExpired is on.
• REAPPEARED: a record that was previously marked EXPIRED and has now been found again. This can only happen after an earlier run with emitExpired on actually marked that record EXPIRED during a complete scan. A search that never turns emitExpired on will only ever see NEW, UPDATED and UNCHANGED, never REAPPEARED.

What is compared. Every output field of the record (price, status, dates, photos, rooms, estimate price and so on) is compared with the saved copy, and the fields that differ are listed in changedFields. Days on market and its text (domText), the day counters (dateAddedDays, dateListDays, dateEndDays), the estimate popularity score and estimate date, and the per-card scores change on their own with the clock, so they are left out of the comparison: they stay in your output, but they never make a record UPDATED. Add your own noisy fields under Ignore fields when detecting changes (ignoreFieldsForChanges); use a dotted path for a nested field (estimate.confidence, or rooms.size for every room). Changing this list never causes a one-time wave of UPDATED rows, because the saved copy is re-compared with the current list.

EXPIRED is never guessed from a partial scan. A run that was capped by Max results or Max pages, stopped on a repeated page, lost a result page or a location/agent/community/listing (could not be fetched or resolved), or hit a search that returns its maximum of 4000 results, does not mark anything EXPIRED; the previous state of those records is kept.

Every record also carries firstSeenAt / lastSeenAt in incremental mode. The detail-enrichment surcharge is billed only for records that actually reach the dataset; a suppressed UNCHANGED record's detail page may still be fetched (needed to compute the fingerprint) but is never charged.

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 (the listing's link for property records, or the agent's title or name for agent records) and its key fields flattened to plain text (price, beds and baths, URL, and more). Nested objects collapse to their main value, and long lists trim to the first few names. The complete record always stays in the Apify dataset; the connector copy is a readable digest for browsing in your app.

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; the export only runs when a connector is selected.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search, url, detail, agent, or community.
province	string	ON	ON, BC, or AB.
locations	array	none (prefill: ["Toronto"])	City or community names. Empty searches the whole province. Used by search and community modes.
status	array	["for-sale"]	for-sale, for-rent, sold, leased, de-listed; de-listed is split into its own delisted statuses.
propertyTypes	array	[]	Detached, Semi-Detached, Freehold Townhouse, Condo Townhouse, Condo Apt, Link, Multiplex, Vacant Land, Other. Empty means all types.
minPrice	integer	none	Minimum price in CAD.
maxPrice	integer	none	Maximum price in CAD.
minBedrooms	integer	none	Minimum bedrooms (5 means 5+).
maxBedrooms	integer	none	Maximum bedrooms (5 means 5+).
minBathrooms	integer	none	Minimum bathrooms.
minGarage	integer	none	Minimum garage spaces.
minSqft	integer	none	Minimum interior size in square feet.
maxSqft	integer	none	Maximum interior size in square feet.
listingDays	integer	none	Only listings first listed within the last N days (0 or empty means any age).
listingType	string	all	all, assignment (pre-construction assignment sales) or resale.
community	string	none	Narrow a city search to one community, e.g. Alliance with location Barrie. If it is not found the whole city is searched.
soldDays	integer	90	For sold / leased / de-listed status: only include records from the last N days.
sortBy	string	newest	newest, price-asc, price-desc.
urls	array	one example of each supported link type (see Supported URL shapes)	Listing links, city or area pages, province map pages, agent profiles or the agents directory. Used by url mode.
listings	array	[]	Listing IDs or full listing links. Used by detail mode.
agents	array	[]	Agent profile links or bare slugs. Leave empty to scrape the whole province agent directory instead. Used by agent mode.
agentCategory	string	sold	Which of a named agent's listings to pull: sold, active, or toured.
fetchDetails	boolean	true	Open each listing's detail page for photos, rooms, schools, price history, community stats and the HouseSigma estimate. Turn off for a faster, lighter run of search-card fields only.
maxItems	integer	50	Stop after this many records. 0 means no limit.
maxPages	integer	none	Maximum result pages (20 listings each) to walk per location. Leave empty (or 0) to walk every result page, up to a hard cap of 200 pages per location; higher values are clamped to 200.
resumeFromRunId	string	none	A previous run ID or dataset ID to continue a full-catalogue walk across separate runs. Records already collected there (matched by listing, agent, or community ID) are skipped, so this run only saves the new ones.
incrementalMode	boolean	false	Turn on for daily or recurring monitoring of the same search. See "Resume and Incremental mode" above.
stateKey	string	none	Optional. Name an incremental-mode monitoring campaign, or share state across differently configured runs. Leave empty to derive a key automatically from the search mode, locations and filters.
emitUnchanged	boolean	false	Incremental mode only. Also return (and bill) records that have not changed since the last run, marked UNCHANGED.
emitExpired	boolean	false	Incremental mode only. Also return (and bill) records present in a previous run but no longer found, marked EXPIRED. Only produced when a run fully scans the tracked search.
ignoreFieldsForChanges	string[]	[]	Incremental mode only. Extra field names (dotted path for nested fields) that never trigger UPDATED; they stay in the output. Days on market and its text, the day counters (dateAddedDays, dateListDays, dateEndDays), estimate popularity score and date, and per-card scores are always ignored.
proxy	object	Apify Proxy	Connection settings. The default works on paid plans; residential (optionally pinned to Canada) is supported but not required.
mcpConnectors	array	none	Optional: send a summary of each record to apps you authorized under Integrations.
notionParentPageUrl	string	none	Notion connector only: page under which item pages are created.
maxNotifyListings	integer	50	Cap on items written to each connector per run. Does not affect the dataset.

Output Example

Sample shape: values are illustrative placeholders, not from a live listing.

{
  "idListing": "00000000000000AB",
  "url": "https://housesigma.com/on/toronto-real-estate/1-sample-st/home/00000000000000AB/",
  "status": "For Sale",
  "saleOrLease": "Sale",
  "propertyType": "Detached",
  "address": "1 Sample Street",
  "municipality": "Toronto",
  "community": "Sample Community",
  "province": "Ontario",
  "mlNum": "X00000000",
  "bedrooms": 3,
  "bathrooms": 2,
  "priceListed": 1200000,
  "priceListedText": "1,200,000",
  "priceSold": "(Sign-in required)",
  "latitude": 43.6500,
  "longitude": -79.3800,
  "sizeText": "1500 ft²",
  "dateListed": "2026-01-01",
  "daysOnMarket": 12,
  "photos": ["https://cache16.housesigma.com/file/pix/00000000/0000_1.jpg"],
  "virtualTour": null,
  "keyFacts": { "Tax": "$0,000 / 2025", "Lot Size": "00 x 000 feet", "Parking": "2 garages" },
  "rooms": [{ "type": "Living", "level": "Main", "dimensions": "0.00 x 0.00" }],
  "priceHistory": [{ "price": "1,200,000", "status": "For Sale", "date_start": "2026-01-01" }],
  "estimate": { "priceInt": 1180000, "confidence": 0.8, "rentInt": 3500 }
}

Plan Requirement

A paid Apify plan is required, because the actor reads pages through Apify Proxy and free plans do not include proxy access. The default Apify Proxy setting is enough: datacenter connections load listings, agents and community data, and residential is not required. If the selected connection is refused, the log says: The selected connection is unavailable to this run. Apify free plans do not include residential proxies. Continuing on a backup connection; some pages may still be unavailable. If no page can be read at all, the run fails with one of these messages instead of finishing with an empty dataset:

• The proxy connection was refused for this account, so no page could be read. Your Apify plan does not include proxy access; a paid plan is required: https://apify.com/pricing. If you entered your own proxy URLs, check that their credentials are valid.
• No results: residential proxies are unavailable on this run (Apify free plans do not include them), and the backup connection could not load the requested HouseSigma pages. Upgrade at https://apify.com/pricing or supply your own proxy URLs, then try again.
• Could not load any results page (the requests failed), so nothing was collected. This is a connection problem, not an empty search. Please try again later.

FAQ

How much does it cost?

You pay per record returned, and the optional full-detail payload (photos, rooms, price history, estimate and more) carries a separate detail-enrichment charge that only applies to records that actually reach the dataset. Current rates: $0.002 per record, $0.0007 per record for the detail-enrichment charge (only when full details are on), and a $0.05 actor-start charge per run (BRONZE tier prices, tiered by Apify plan). The Pricing tab always shows the live rates. Use Max results to cap the cost of any run.

Is it legal to scrape HouseSigma?

This actor collects only publicly available listing data. You are responsible for how you use it: follow HouseSigma's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution. Listing facts such as price and size are generally factual data, but photos and some third-party content may carry separate rights.

Can I get only new or changed listings on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental mode. Each run then returns only new and updated records, and unchanged ones are not billed. Turning on emitExpired also reports listings that dropped out of the tracked search, but only once a run has fully scanned it, and only a record that was previously marked EXPIRED this way can later come back as REAPPEARED.

What's the difference between Resume and Incremental mode?

Resume (resumeFromRunId) continues one specific interrupted run so it doesn't re-scrape what it already saved. Incremental mode is for running the same search again and again on a schedule and getting a diff each time. Turning both on together only works to bootstrap a brand-new monitoring campaign from a resumed dataset; if incremental state already exists for that search, the run fails with a clear message asking you to drop resumeFromRunId or pick a different stateKey.

Why did my run fail instead of returning an empty dataset?

The run fails immediately, with a clear message, if it cannot open a session with HouseSigma at all, or if resumeFromRunId doesn't point to a run or dataset your account can read, or if Incremental mode and Resume are combined in a way that would conflict with existing saved state. Once a session is open, an individual request that gets refused is retried and, if it still fails, skipped with a warning instead of failing the whole run, so a search that partially succeeds returns whatever it could read rather than nothing at all.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

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