# Zap Imóveis, VivaReal & QuintoAndar Scraper - Imóveis Brasil (`kalilfagundes.w/imoveis-brasil-scraper`) Actor

\[Limited Launch Offer $1.50/1K] Scrape Brazil real estate listings from Zap Imóveis, VivaReal and QuintoAndar in one format: price, condo fee, IPTU, area, rooms, address, photos. Rent or sale, duplicates removed.

- **URL**: https://apify.com/kalilfagundes.w/imoveis-brasil-scraper.md
- **Developed by:** [Scrape With Me](https://apify.com/kalilfagundes.w) (community)
- **Categories:** Real estate, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.28 / 1,000 listings

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Zap Imóveis, VivaReal & QuintoAndar Scraper - Imóveis Brasil

**PT:** Extraia anúncios de imóveis do **Zap Imóveis**, **VivaReal** e **QuintoAndar** em um único formato: preço, condomínio, IPTU, custo mensal total, área, quartos, banheiros, vagas, endereço com CEP e coordenadas, fotos e anunciante. Aluguel ou venda, filtros, **duplicados removidos** (Zap e VivaReal compartilham anúncios).

**EN:** Scrape Brazilian real-estate listings from **Zap Imóveis, VivaReal and QuintoAndar** in one standard format: price, condo fee, IPTU, total monthly cost, area, rooms, address with ZIP and coordinates, photos and advertiser. Rent or sale, filters and cross-portal duplicate removal. No login, no browser.

### Por que este / Why this one

- **Três portais, um formato.** Compare preços entre portais sem planilhas manuais.
- **Locais em texto.** Digite "Pinheiros, São Paulo" ou "Curitiba" - o próprio autocomplete dos portais resolve o local.
- **Sem duplicados** entre Zap e VivaReal.

### Exemplo de entrada / Input example

```json
{
  "locations": ["Pinheiros, São Paulo", "Curitiba"],
  "portals": ["zap", "vivareal", "quintoandar"],
  "business": "rent",
  "propertyTypes": ["apartment"],
  "priceMax": 6000,
  "bedroomsMin": 2,
  "maxItemsPerSearch": 200
}
```

### Exemplo de saída / Output example

```json
{
  "portal": "zap",
  "id": "2915456134",
  "url": "https://www.zapimoveis.com.br/imovel/aluguel-apartamento-1-quarto-mobiliado-pinheiros-...-id-2915456134/",
  "title": "Apartamento com 1 Quarto para alugar, 38m²",
  "business": "rent",
  "price": 4900,
  "condoFee": 740,
  "iptuYearly": 325,
  "totalMonthlyCost": 5640,
  "area": 38,
  "bedrooms": 1,
  "bathrooms": 1,
  "parkingSpaces": 1,
  "propertyType": "APARTMENT",
  "amenities": ["GYM", "POOL", "FURNISHED", "CONCIERGE_24H"],
  "street": "Rua Eugênio de Medeiros",
  "streetNumber": "288",
  "neighborhood": "Pinheiros",
  "city": "São Paulo",
  "zipCode": "05425000",
  "lat": -23.568823,
  "lon": -46.700156,
  "images": ["https://resizedimgs.zapimoveis.com.br/img/vr-listing/..."],
  "advertiser": "Olimpia House",
  "advertiserLicense": "29559-J-SP",
  "createdAt": "2026-10-02T08:07:56.010+00:00",
  "searchLocation": "Pinheiros, São Paulo",
  "scrapedAt": "2026-10-04T20:50:00Z"
}
```

### Preço / Pricing

Pay per event, platform usage included: one `listing` event per saved listing (see the **Pricing** tab). Duplicates and listings removed by your filters are not charged.

### Limitações / Limitations

- QuintoAndar searches by map area: a neighborhood search also returns listings in neighboring areas; it shows rent/total cost but not every detail (no condo/IPTU split, one cover photo).
- Zap/VivaReal pages are read 30 listings at a time; very deep result pages (beyond ~2,000) are not served by the portals - split by neighborhood.
- Imovelweb and Chaves na Mão are not included yet.

### Related actors

- [Amazon Price Tracker & Product Scraper - ASIN, BSR, 23 Sites](https://apify.com/kalilfagundes.w/amazon-product-scraper)
- [Indeed & LinkedIn Jobs Scraper - Glassdoor, Naukri, Bayt](https://apify.com/kalilfagundes.w/job-boards-scraper)
- [Walmart Product Search Scraper - Prices, Ratings, Sellers](https://apify.com/kalilfagundes.w/walmart-scraper)

### Feedback

**PT:** Se este actor te poupa tempo, uma avaliação rápida na página da Store ajuda outras pessoas a encontrá-lo. Algo não funcionou? Abra um chamado na aba **Issues**.

**EN:** If this actor saves you time, a quick rating on its Store page helps other people find it. Something not working? Open an issue in the **Issues** tab.

### Run it on a schedule and connect it to your tools

**Schedule:** in Apify Console open *Schedules → Create*, pick this actor and your input, and set it to run
every Monday at 07:00 (your time zone) for a fresh dataset on a fixed day. Each run returns the full, current result set as a new dataset.

**Integrations** (Actor → *Integrations* tab, no code):

- **Google Sheets** — append every run's rows to a sheet.
- **Make, Zapier, n8n** — start the actor from a scenario/zap/workflow and use the rows in the next steps.
- **Webhook** — get a POST to your endpoint when a run succeeds, then download the dataset.
- **Slack / email** — notify your team when a scheduled run finishes.

**AI agents (MCP)** — Claude, ChatGPT, Cursor, VS Code or any MCP client can run it as a tool: add the Apify MCP
server `https://mcp.apify.com?actors=kalilfagundes.w/imoveis-brasil-scraper` (sign in with your Apify account) and ask for the data in
plain language. The agent fills the input from the input schema and reads the dataset back.

**API** — call it from your code (`pip install apify-client` / `npm i apify-client`):

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("kalilfagundes.w/imoveis-brasil-scraper").call(run_input={
    "locations": [
        "Pinheiros, São Paulo",
        "Curitiba"
    ],
    "portals": [
        "zap",
        "vivareal",
        "quintoandar"
    ],
    "business": "rent",
    "bedroomsMin": 2,
    "maxItemsPerSearch": 40,
    "maxItems": 200
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

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

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('kalilfagundes.w/imoveis-brasil-scraper').call({
  "locations": [
    "Pinheiros, São Paulo",
    "Curitiba"
  ],
  "portals": [
    "zap",
    "vivareal",
    "quintoandar"
  ],
  "business": "rent",
  "bedroomsMin": 2,
  "maxItemsPerSearch": 40,
  "maxItems": 200
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

# Actor input Schema

## `locations` (type: `array`):

Bairro e cidade ou só a cidade, um por linha: "Pinheiros, São Paulo", "Curitiba".

## `portals` (type: `array`):

Zap and VivaReal share most listings (duplicates are removed).

## `business` (type: `string`):

Rent or sale listings.

## `propertyTypes` (type: `array`):

Empty = all types.

## `priceMin` (type: `integer`):

R$ (rent per month or sale price).

## `priceMax` (type: `integer`):

R$ (rent per month or sale price).

## `bedroomsMin` (type: `integer`):

Minimum number of bedrooms.

## `areaMin` (type: `integer`):

Minimum usable area in m².

## `areaMax` (type: `integer`):

Maximum usable area in m².

## `maxItemsPerSearch` (type: `integer`):

Listings to read per location and portal (before filters).

## `maxItems` (type: `integer`):

Stop after this many saved listings. 0 = no limit.

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

Requests start direct; the proxy (Brazil exit) is used on retries.

## Actor input object example

```json
{
  "locations": [
    "Pinheiros, São Paulo"
  ],
  "portals": [
    "zap",
    "quintoandar"
  ],
  "business": "rent",
  "maxItemsPerSearch": 20,
  "maxItems": 500,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (type: `string`):

OUTPUT record: fetched / matched / saved / duplicates per location and portal.

# 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 = {
    "locations": [
        "Pinheiros, São Paulo"
    ],
    "maxItemsPerSearch": 20,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("kalilfagundes.w/imoveis-brasil-scraper").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 = {
    "locations": ["Pinheiros, São Paulo"],
    "maxItemsPerSearch": 20,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("kalilfagundes.w/imoveis-brasil-scraper").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 '{
  "locations": [
    "Pinheiros, São Paulo"
  ],
  "maxItemsPerSearch": 20,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call kalilfagundes.w/imoveis-brasil-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kalilfagundes.w/imoveis-brasil-scraper"
        }
    }
}
```

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/7ozweCJ4RqGKNTWag/builds/XpXP0JDqgdEWS8Dfx/openapi.json