PropTech Data Feed

Real Estate Listing Data Feed for Property Portals and Apps

If you're building a property portal, home search app, or any PropTech product that needs listing data, the data is locked behind platforms that block automated access or charge enterprise prices. Specrom gives you pre-scraped, normalized MLS listing data through a clean API. Daily updates. No enterprise contract. No scraper maintenance on your end.

50+ Structured fields per listing
Daily MLS data refresh
US-wide MLS coverage
// Sample listing from Specrom Real Estate API
{
  "property_id": "3173751224",
  "status": "for_sale",
  "list_price": 3650000,
  "price_per_sqft": 1471,
  "description": {
    "beds": 4, "baths": 4,
    "sqft": 2482,
    "type": "single_family",
    "year_built": 1920
  },
  "location": {
    "address": { "line": "1815 E 3rd St",
      "city": "Brooklyn", "state_code": "NY" },
    "coordinate": { "lat": 40.605971,
      "lon": -73.97002 }
  },
  "photo_count": 22,
  "flags": { "is_new_listing": true,
    "is_price_reduced": false }
}

Trusted by PropTech teams building on real data

50+ Fields per Listing
Daily MLS Refresh
US-Wide Coverage
REST API / Bulk CSV
MLS Disclaimer Included

50+ Structured Fields. Everything a Portal Needs to Go Live.

Each listing in the feed includes 50+ structured fields covering everything a property portal needs from day one. The data is pre-parsed and normalized — no HTML scraping, no field mapping, no schema surprises.

  • Core listing: Property ID, MLS ID, status, list price, price per sqft, days on market, list date, last price change
  • Property details: Beds, baths, sqft, lot sqft, property type, year built, stories, garage, pool, heating, cooling
  • Location: Full address, lat/lon coordinates, county, FIPS code, neighborhood names, Street View URL
  • Photos: Photo count + full URL array, ready for gallery rendering
  • Schools: Assigned school list (by district) and nearby schools list
  • Mortgage estimates: Monthly payment breakdown — P&I, property tax, home insurance, HOA, mortgage insurance
  • MLS source: MLS name, listing ID, and disclaimer text for display compliance
// Mortgage estimate object
"mortgage": {
  "estimate": {
    "monthly_payment": 19216,
    "loan_amount": 2920000,
    "down_payment": 730000,
    "monthly_payment_details": [
      { "type": "principal_and_interest",
        "amount": 17415 },
      { "type": "home_insurance",
        "amount": 1186 },
      { "type": "property_tax",
        "amount": 615 }
    ]
  }
},
// MLS source (required for display compliance)
"source": {
  "name": "Brooklyn MLS",
  "type": "mls",
  "listing_id": "499022",
  "disclaimer": "© 2026 Brooklyn MLS..."
}

From API Call to Live Listings in Your App

No scraper infrastructure to maintain. No anti-bot arms race. No front-end breakage when Zillow ships a redesign. Just a REST API that returns clean data.

1

Filter by Geography

Query by state, ZIP code, metro area, or bounding box. Filter by listing status, price range, or property type. Paginated responses for bulk pulls.

2

Store in Your Database

Ingest listings into your own database and power your search UI. Subscribe to delta feeds to receive only new listings, price changes, and status changes rather than pulling the full dataset daily.

3

Render and Ship

Use coordinates for map display, photo arrays for galleries, description fields for search indexing, and the MLS disclaimer text for display compliance. Everything you need is in the response.

Four Ways PropTech Teams Use This Data

Whether you're building a consumer-facing portal or a B2B analytics product, the same feed powers different integration patterns depending on what you're building.

🏠

Property Search Portal

Pull active listings by metro or ZIP, store in your own database, power your search UI. Use coordinates for map display, photo arrays for galleries, and description fields for search indexing.

Ideal for: Home search apps, MLS portal alternatives

Listing Alerts Product

Subscribe to daily delta feeds for specific geographies. Get only new listings, price changes, and status changes rather than pulling the full dataset on every refresh cycle.

Ideal for: Buyer alert tools, price tracker apps
📊

Valuation Tool

Use the listing data alongside the three AVM estimates in the feed (Quantarium, Cotality, Collateral Analytics) to show users how listed price compares to independent estimates.

Ideal for: Home valuation tools, AVM-based products
🗺️

Neighborhood Explorer

Combine listing coordinates with neighborhood names, school data, flood risk scores, and noise scores to build a rich location context layer around any property.

Ideal for: Neighborhood analytics, location intelligence tools

What You're Actually Signing Up For When You Scrape Directly

If you're a developer, the temptation is to scrape directly. Here's what you're actually signing up for.

Zillow and Realtor.com run enterprise anti-bot systems. IP blocks, browser fingerprinting, CAPTCHAs, and silent data poisoning — where detected bots get served fake or corrupted results — are all in play. Bypassing them requires residential proxies, browser automation infrastructure, and constant maintenance as sites update their structure.

Scraper breakage is not a one-time event. Real estate sites update their frontends often enough that you can expect to spend engineering time every month just keeping the scrapers running, not shipping features.

Beyond the infrastructure cost, you're operating in legal gray area. The ToS for major listing platforms explicitly prohibit scraping. For a commercial product, that risk is real.

We've already built and maintained this infrastructure for years. You get the data through a stable API with a consistent schema you can build on.

  • IP blocks and fingerprinting — Zillow and Realtor.com run enterprise anti-bot systems. Residential proxies and browser automation are the minimum entry point.
  • Silent data poisoning — Detected bots get served fake or corrupted results. You won't know until you see bad data downstream.
  • Constant maintenance — Real estate sites update their frontends regularly. Expect to spend engineering time every month keeping scrapers alive.
  • Legal exposure — The ToS for major listing platforms explicitly prohibit scraping. For a commercial product, that risk is real and not theoretical.
  • We've already solved this — Specrom maintains the infrastructure. You get a stable API with guaranteed uptime and no maintenance burden.
// What you get with Specrom instead:

GET /listings
  ?state=NY
  &status=for_sale
  &min_price=500000
  &max_price=2000000
  &property_type=single_family

// Returns paginated, normalized records:
{
  "total": 4821,
  "page": 1,
  "per_page": 100,
  "listings": [
    // ...50+ fields per listing
  ]
}

Frequently Asked Questions

The feed includes 50+ structured fields per listing: property ID and MLS ID, listing status, list price and price per sqft, days on market, full address, lat/lon coordinates, beds, baths, sqft, lot sqft, year built, property type, stories, photo count and photo URLs, school data (assigned and nearby), and mortgage estimates with full payment breakdowns. MLS source name and disclaimer text are included for display compliance.

The full listing feed refreshes daily. Delta feeds are also available — these deliver only new listings, price changes, status changes, and delistings since the last pull, which is more efficient for products that run daily ingestion jobs.

Yes. The API supports filtering by state, ZIP code, metro area, or bounding box coordinates. You can also filter by listing status (for sale, pending, contingent, coming soon), price range, and property type (single family, condo, townhouse, multi-family, land, and more).

Yes. Each listing record includes the MLS source name, MLS listing ID, and the MLS disclaimer text required for display compliance. This is included in the source object of every record.

A full pull returns all active listings matching your filter criteria. A delta feed returns only records that have changed since your last pull — new listings, price changes, status changes (e.g. pending, sold), and delistings. For products running daily ingestion, delta feeds are significantly more efficient.

Specrom covers major MLS regions across the US, refreshed daily. Coverage is broad but not uniform across every small regional MLS. If you need coverage confirmed for specific metros or ZIP code sets before integrating, reach out and we'll verify availability for your target markets.

Yes. You can request a free sample dataset with no sales call required — just data you can evaluate before committing. We can also provide API trial access so you can make live queries against your target geographies before signing up.

Get a Free Sample Dataset

Tell us what you're building and your target markets. We'll send a sample within 24 hours.

  • Free sample dataset — evaluate field quality before you commit
  • API trial access — live queries against your target geographies
  • Full schema documentation with data types and sample values
  • Delta feed support for efficient daily ingestion
  • No enterprise contract, no minimum commitment
  • Response within 24 hours

Request a Quote

We'll respond with a sample dataset and API credentials within 24 hours.

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Thank you!