Real Estate Scraping APIs — Zillow, Realtor, and MLS Data

Real estate data — property listings, prices, market trends, agent information — is fragmented across dozens of platforms. Zillow, Realtor.com, Redfin, and local MLS systems each hold pieces of the puzzle, and none of them make it easy to get structured data at scale.

This guide covers every realistic approach to getting real estate data via API in 2026, from official APIs to scraping solutions.

Key Takeaways

• Zillow's official API (Bridge Interactive) exists but requires broker partnerships — not accessible to individual developers
• RapidAPI hosts several real estate data APIs that aggregate Zillow, Realtor.com, and Redfin data — easiest starting point
• SearchHive ScrapeForge can scrape public listing pages when the official APIs are unavailable or insufficient
• Apify has pre-built Zillow and Realtor.com actors that handle the parsing complexity
• Bright Data offers real estate datasets that pre-collect listing data at scale

The Real Estate Data Problem

Real estate data is harder to access than most verticals for three reasons:

1. Fragmentation — No single source covers everything. Zillow has good coverage but gaps in rural areas. Realtor.com pulls from MLS feeds but has rate limits. Redfin has its own dataset. Local MLS systems are their own silos.

2. Anti-scraping — Zillow and Realtor.com employ aggressive anti-bot measures. They rotate page structures, use behavioral fingerprinting, and serve CAPTCHAs frequently.

3. Legal complexity — Real estate listing data is often copyrighted by the MLS or listing broker. Terms of service vary by platform.

Option 1: Official APIs

Zillow API (Bridge Interactive)

Zillow's API is available through Bridge Interactive, their official data partner. It provides access to active listings, property details, and market data.

Access requirements:

• Must be a licensed broker or technology partner
• Requires application and approval
• Not available to individual developers or hobbyists
• Pricing is custom (contact Bridge Interactive)

Verdict: If you're building a product for the real estate industry and can establish a broker partnership, this is the cleanest path. If you're a developer building analytics tools or market research products, this door is effectively closed.

Realtor.com API

Realtor.com offers an official API through their developer program (moved to Move Inc.'s platform).

Access requirements:

• Developer registration required
• Rate limits are restrictive on free tiers
• Data is sourced from MLS feeds — coverage is good but not universal
• Historical data is limited

import requests

# Realtor.com API (via RapidAPI or official endpoint)
resp = requests.get(
    "https://realtor.p.rapidapi.com/properties/v3/list",
    headers={"X-RapidAPI-Key": "your_key"},
    params={
        "limit": 20,
        "offset": 0,
        "city": "Austin",
        "state_code": "TX",
        "status": "for_sale"
    }
)

for listing in resp.json().get("data", {}).get("results", []):
    print(f"{listing['address']}: ${listing['price']:,}")
    print(f"  Beds: {listing['beds']} | Baths: {listing['baths']} | Sqft: {listing['sqft']}")

Pricing: Varies by provider. RapidAPI plans typically start at $10-30/mo.

Zillow Public Data (Unofficial)

Zillow's website exposes some data through undocumented endpoints. This is what most scraping tools actually use.

import requests

# Zillow search endpoint (undocumented, may change)
resp = requests.get(
    "https://www.zillow.com/search/GetSearchPageState.htm",
    params={
        "searchQueryState": '{"filterState": {"status": {"value": "ForSale"}}, "mapBounds": {"west": -97.8, "east": -97.6, "south": 30.2, "north": 30.4}}',
        "wants": '{"cat1": ["listResults"]}',
    },
    headers={"User-Agent": "Mozilla/5.0"}
)

Warning: This is fragile. Zillow changes these endpoints regularly. Not recommended for production without a scraping API that handles the maintenance.

Option 2: RapidAPI Marketplace

RapidAPI hosts several real estate APIs that aggregate data from Zillow, Realtor.com, and other sources. They handle the scraping complexity and provide a stable API interface.

Popular real estate APIs on RapidAPI:

import requests

# Using a Zillow API from RapidAPI
resp = requests.get(
    "https://zillow-working-api.p.rapidapi.com/property",
    headers={"X-RapidAPI-Key": "your_key"},
    params={"zpid": "20454914"}  # Zillow Property ID
)

property_data = resp.json()
print(f"Address: {property_data['address']}")
print(f"Price: ${property_data['price']:,}")
print(f"Zestimate: ${property_data['zestimate']:,}")

Pros: Stable API interface, someone else handles scraping maintenance, multiple data sources. Cons: Additional layer = additional cost, dependent on the API provider's scraping success, data freshness varies.

Option 3: SearchHive ScrapeForge

/blog/best-web-scraping-apis-with-python-sdk-2026

When official APIs don't cover what you need, SearchHive's ScrapeForge can scrape public listing pages from Zillow, Realtor.com, Redfin, and other real estate sites.

import requests

headers = {"Authorization": f"Bearer {API_KEY}"}

# Scrape a Zillow listing page
resp = requests.post(
    "https://api.searchhive.dev/v1/scrapeforge",
    headers=headers,
    json={
        "url": "https://www.zillow.com/homedetails/123-Main-St/20454914_zpid/",
        "output_format": "markdown",
        "js_render": True
    }
)

page_data = resp.json()
print(page_data["markdown"][:500])

# Extract structured data with DeepDive
resp = requests.post(
    "https://api.searchhive.dev/v1/deepdive",
    headers=headers,
    json={
        "url": "https://www.zillow.com/homedetails/123-Main-St/20454914_zpid/",
        "extract": {
            "address": "string",
            "price": "integer",
            "bedrooms": "integer",
            "bathrooms": "integer",
            "square_feet": "integer",
            "lot_size": "string",
            "year_built": "integer",
            "days_on_market": "integer",
            "description": "string"
        }
    }
)

listing = resp.json()
print(f"{listing['address']}: ${listing['price']:,}")
print(f"{listing['bedrooms']} bed / {listing['bathrooms']} bath / {listing['square_feet']} sqft")

Batch scraping for market analysis:

import requests
import json

headers = {"Authorization": f"Bearer {API_KEY}"}

# Generate URLs for all listings in a search
zillow_urls = [
    f"https://www.zillow.com/homedetails/{zpid}_zpid/"
    for zpid in ["20454914", "20849302", "20624755", "20198312", "20987432"]
]

# Batch scrape
resp = requests.post(
    "https://api.searchhive.dev/v1/scrapeforge/batch",
    headers=headers,
    json={
        "urls": zillow_urls,
        "output_format": "markdown"
    }
)

for result in resp.json().get("results", []):
    if result.get("success"):
        print(f"{result['url']}: {len(result['markdown'])} chars")

Pricing: $9/mo (5K credits) to $49/mo (100K credits). A Zillow listing scrape with JS rendering costs roughly 2-5 credits. At Builder tier, that's roughly 20,000-50,000 listings per month for $49.

Option 4: Apify Real Estate Actors

Apify has several pre-built actors for real estate data collection:

• Zillow Scraper — Extracts listings, property details, and Zestimates
• Realtor.com Scraper — Active listings and property data from Realtor.com
• Redfin Scraper — Listings from Redfin's platform

from apify_client import ApifyClient

client = ApifyClient("your_token")

# Run Zillow scraper for a specific location
run = client.actor("danek/zillow-scraper").call(run_input={
    "searchLocation": "Austin, TX",
    "maxItems": 100,
    "type": "for_sale"
})

dataset = client.dataset(run["defaultDatasetId"])
for item in dataset.iterate_items():
    print(f"{item.get('address', 'N/A')}: ${item.get('price', 0):,}")

Pricing: $49/mo (50 compute units). A Zillow listing typically uses 0.02-0.1 CU. $49/mo gets you roughly 500-2,500 listings.

Option 5: Bright Data Real Estate Datasets

Bright Data maintains pre-collected real estate datasets covering Zillow, Realtor.com, and other platforms.

Available data:

• Property listings (address, price, beds, baths, sqft)
• Market trends (median prices, days on market, inventory)
• Agent and broker information
• Historical pricing data

Pricing: Custom enterprise pricing. Contact sales for dataset access.

Pros: High data quality, maintained by Bright Data's infrastructure, includes historical data. Cons: Enterprise pricing only, not real-time, limited to available datasets.

Best Practices for Real Estate Scraping

1. Respect robots.txt generator and terms of service Check each platform's robots.txt and terms. Zillow and Realtor.com both prohibit automated scraping in their ToS. Use pre-collected datasets where possible to minimize legal risk.

2. Rate limit aggressively Real estate platforms have some of the most aggressive anti-bot systems on the web. Use delays (2-5 seconds between requests), rotate user agents, and use residential proxies.

3. Validate data across sources No single source is authoritative. Cross-reference Zillow prices with Realtor.com and Redfin when possible. Zestimates and Redfin Estimates can differ by 5-15%.

4. Cache aggressively Real estate data changes daily, not second-by-second. Cache listings and only refresh them every 24-48 hours. This reduces your API costs by 10-20x.

5. Use structured extraction Don't parse raw HTML yourself. Use an API with built-in extraction (SearchHive DeepDive) or a pre-built scraper (Apify actors) that handles the DOM parsing.

Comparison Table

Recommendation

For production real estate platforms: Use the official Zillow API if you can get broker access. Otherwise, RapidAPI's aggregated real estate APIs provide the most stable interface with reasonable pricing.

For analytics and market research: SearchHive ScrapeForge + DeepDive gives you the cheapest real-time scraping with structured extraction. At ~$0.001/listing, you can afford to scrape thousands of listings for market analysis without breaking your budget.

For ongoing data pipelines: Apify's Zillow and Realtor.com actors handle the maintenance burden (parsing changes, anti-bot updates) and integrate with their scheduling and dataset storage.

Start with SearchHive's free tier — 500 credits to test real estate scraping, no credit card required.

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Updated April 2026. Real estate data access changes frequently — verify current API availability before building production systems.