Zumper Apartment Listings Scraper

Zumper Apartment Listings Scraper

Scrape Zumper apartment listings from any US city, up to a million per run. Every listing returns rent price, beds, baths, square footage, amenities, and property details. Export to CSV, JSON, Excel, or XML.

Zumper's rental marketplace covers thousands of US cities, but manually collecting listings for market research or lead generation is slow. This actor reads the public apartment feeds directly by city slug, so you get structured rental data without building a scraper yourself. It returns every listing in one consistent flat schema, ready for analysis.

Who uses it	What they scrape Zumper for
Market researchers	Track rent trends and inventory levels across US metro areas.
Real estate investors	Compare asking rents and unit mixes in target neighborhoods.
Property managers	Benchmark competitor pricing and amenity packages.
Data analysts	Build rental market datasets for dashboards and forecasting models.

What it does

This Actor collects Zumper rental listings by city and returns each apartment as a flat row with rent, beds, baths, square footage, and property details.

• 🏙️ City-level targeting: supply a city slug like new-york-ny or los-angeles-ca and pull every available listing.
• 🔢 Flexible volume: set a maximum from 1 to 1,000,000 listings per run to control dataset size and runtime.
• 📦 Flat row output: each listing lands as one row with rent, beds, baths, square footage, and property details, no nested objects to unpack.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Zumper data

📊 Monitor rent trends by city.

A market researcher runs the actor weekly on a set of city slugs to track median rent, unit mix, and inventory changes over time.

🏠 Find investment opportunities.

An investor pulls all listings in a target zip code to identify underpriced units and neighborhoods with rising rents.

📋 Benchmark competitor properties.

A property manager scrapes listings near their buildings to compare asking rents, amenities, and unit availability.

🗺️ Build a rental market dataset.

A data analyst collects listings across multiple cities to feed a pricing model or market dashboard.

Why choose this scraper

	What you get
No API key required	Reads Zumper's public listing feeds directly with no registration or OAuth.
Consistent schema	Every run returns the same flat fields so your pipeline never breaks on schema drift.
Scalable collection	Pull up to a million listings in a single run for metro-wide market coverage.
Multi-format export	Download results as CSV, JSON, Excel, or XML for any analysis tool.

How it compares

Three other Zumper scrapers exist on Apify. Here is how this actor compares on the capabilities their listings describe.

Feature	ParseForge	Zumper Scraper with Contacts	Zillow & Zumper Scraper	Zumper Rental Scraper
City-level scraping	Yes, by city slug	Yes	Yes	Yes
Up to 1M listings per run	Yes	Not listed	Not listed	Not listed
Contact data extraction	Not listed	Yes	Not listed	Not listed
Zillow for-sale listings	No, Zumper only	No, Zumper only	Yes	No, Zumper only
Ratings and verification status	Not listed	Not listed	Not listed	Yes
Airbnb-friendly filter	Not listed	Not listed	Not listed	Yes

Configure the run

Drive the Actor with a Zumper city slug and a maximum listing count. The city filter runs before collection so only listings from that market reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
 "city": "new-york-ny",
 "maxItems": 10
}

A larger pull:

{
 "city": "new-york-ny",
 "maxItems": 200
}

Pricing

Pay-per-result: $0.021 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$2.10
1,000 results	$21.00
10,000 results	$210.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Zumper Apartment Listings Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Zumper through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/zumper-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your city slug matches a valid Zumper market URL exactly. Try visiting zumper.com with that slug in your browser. If the page shows listings, the slug is correct. Also confirm your maxItems is set above zero.

The actor runs but collects fewer listings than expected.

Zumper may paginate or limit visible listings for a city. The actor collects what is publicly available. Try a broader city slug or check if Zumper's inventory in that market is smaller than your maxItems setting.

Some fields are empty in my results.

Zumper listings do not always include every detail. Square footage, amenities, or other fields may be blank when the landlord did not provide them. This is normal and reflects the source data.

The actor times out on large cities.

Lower your maxItems to reduce runtime, or increase the actor's timeout setting in the run options. Very large markets with thousands of listings may need more time to complete.

My city slug has spaces or special characters and fails.

Zumper slugs use lowercase letters and hyphens only. Replace spaces with hyphens and remove any special characters. For example, use saint-louis-mo instead of St. Louis, MO.

FAQ

Question	Answer
How do I find the city slug for a Zumper market?	Go to zumper.com, search for a city, and copy the slug from the URL. For example, the New York page uses new-york-ny, and Los Angeles uses los-angeles-ca.
Can I scrape multiple cities in one run?	The actor accepts one city slug per run. To collect multiple cities, run the actor once per city, or use Apify's scheduler to chain runs for each market you need.
What data fields does each listing include?	Each row returns rent price, number of bedrooms and bathrooms, square footage, property address, and available amenities. The exact fields appear in the sample output on the actor's page.
Does this actor require a Zumper account or API key?	No. It reads Zumper's public listing pages directly, so there is no login, API registration, or key to manage.
How many listings can I collect per run?	You set the maximum, from 1 up to 1,000,000. The actor stops when it hits your limit or exhausts the city's listings, whichever comes first.
Can I filter by price range or number of bedrooms?	The actor collects all available listings for a city. Apply price, bedroom, or other filters in your dataset after export using spreadsheet formulas or a data tool.
How often is the data refreshed?	The actor reads live data from Zumper on each run. Schedule it daily or weekly to keep your dataset current with new and updated listings.
What export formats are supported?	You can export your results to CSV, JSON, Excel, or XML from the Apify dataset tab.
Does this work for Canadian or international Zumper markets?	Zumper focuses on US rental markets. The actor works with any city slug that returns listings on zumper.com, but coverage outside the US is limited.
Can I get contact information for landlords or property managers?	This actor collects publicly visible listing details. Contact information availability depends on what Zumper displays on each listing page.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Zumper, Inc. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.