# Zillow Scraper – Active Listings, Sold Comps & Market Stats (`azharmushtaq/zillow-market-intelligence`) Actor

Scrape Zillow for any US city or ZIP. Returns active listings + sold comps with price, beds, baths, sqft, and DOM — plus a MARKET\_SUMMARY with median prices, sale-to-list ratio, and HOT/WARM/COOL market temperature.

- **URL**: https://apify.com/azharmushtaq/zillow-market-intelligence.md
- **Developed by:** [Azhar Mushtaq](https://apify.com/azharmushtaq) (community)
- **Categories:** Real estate, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Zillow Scraper – Active Listings, Sold Comps & Market Stats

Get structured real estate data for any US city, ZIP code, or neighborhood. Scrapes Zillow for **active for-sale listings** and **recently sold comparables**, then computes the market statistics that investors, agents, and analysts actually use.

### What you get

Every run outputs two types of records:

**LISTING records** (one per property):

- Address, city, state, ZIP
- Property type (Single Family, Condo/Co-op, Townhouse, Multi-Family)
- Price, beds, baths, living area (sqft), year built, price per sqft
- Days on market (0 = listed within last 24 hours)
- Sold date (for sold comps)
- Coordinates + direct Zillow URL

**MARKET\_SUMMARY record** (one per run):

- Median list price, average, min/max
- Median price per sqft
- Median days on market
- Price tier breakdown ($300k / $300–600k / $600k–$1M / $1M+)
- Bedroom breakdown with median price per tier
- Property type breakdown
- **Sold comps stats**: median sold price, sale-to-list ratio, % sold above asking
- **Market temperature**: HOT / WARM / COOL with a plain-English reason

### Example output

```json
{
  "type": "MARKET_SUMMARY",
  "location": "Austin, Travis County",
  "active": {
    "total": 40,
    "median_list_price": 479000,
    "median_price_per_sqft": 308,
    "median_days_on_market": 3
  },
  "sold": {
    "total": 38,
    "median_sold_price": 492000,
    "median_sale_to_list_ratio": 1.03,
    "pct_sold_above_list": 61
  },
  "market_temperature": "HOT",
  "market_temperature_reason": "Median sale price is 3% above list; 61% of homes sold over asking."
}
```

### Who uses this

- **Real estate investors** — screen markets before deeper research
- **Agents and brokers** — pull comp data for any neighborhood in seconds
- **Analysts** — feed structured data into spreadsheets or dashboards
- **Developers** — integrate live Zillow market data into apps via the Apify API

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `location` | string | **required** | City, neighborhood, or ZIP: `"Austin, TX"`, `"Brooklyn, NY"`, `"90210"` |
| `maxListings` | integer | 40 | Max active listings (Zillow returns ~40/page; use multiples of 40) |
| `soldWithinDays` | integer | 90 | Sold comps lookback window (30–365 days) |
| `propertyType` | select | all | `all`, `house`, `condo`, `townhouse`, `multi_family` |
| `proxyConfiguration` | proxy | — | **Residential proxy strongly recommended** — Zillow blocks datacenter IPs |

### Proxy requirement

Zillow uses IP-level blocking. A residential proxy is required for reliable results. Without one, the actor will return a 403 warning in the logs and no listings.

### Typical run time

Under 30 seconds for a single page (40 listings). Multi-page runs scale linearly.

# Actor input Schema

## `location` (type: `string`):

City, neighborhood, or ZIP code to analyze. Examples: 'Austin, TX', 'Brooklyn, NY', '90210'.

## `maxListings` (type: `integer`):

Maximum number of active listings to scrape. Zillow returns ~40 per page; use a multiple of 40 for complete pages. Hard cap: 500.

## `soldWithinDays` (type: `integer`):

How far back to pull recently sold comparables.

## `propertyType` (type: `string`):

Filter by property type. 'all' includes all residential types.

## `proxyConfiguration` (type: `object`):

Proxy settings. Residential proxy is strongly recommended — Zillow blocks datacenter IPs. Without a proxy, runs may return 0 results.

## Actor input object example

```json
{
  "location": "Austin, TX",
  "maxListings": 5,
  "soldWithinDays": 90,
  "propertyType": "all"
}
```

# Actor output Schema

## `listings` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "location": "Austin, TX"
};

// Run the Actor and wait for it to finish
const run = await client.actor("azharmushtaq/zillow-market-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "location": "Austin, TX" }

# Run the Actor and wait for it to finish
run = client.actor("azharmushtaq/zillow-market-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "location": "Austin, TX"
}' |
apify call azharmushtaq/zillow-market-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,azharmushtaq/zillow-market-intelligence"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZdYep7BerAzfsXUK7/builds/8AegwsyNprDxH4HcH/openapi.json