# Fast LoopNet Scraper — Commercial Real Estate & Cap Rates (`rbbscrap/fast-loopnet-scraper`) Actor

Scrape LoopNet commercial real estate listings across the US. Extract asking prices, price per sqft, building size, Cap Rates, property types, zoning, and broker contacts on 256MB RAM.

- **URL**: https://apify.com/rbbscrap/fast-loopnet-scraper.md
- **Developed by:** [Hector](https://apify.com/rbbscrap) (community)
- **Categories:** Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Fast LoopNet Scraper — Commercial Real Estate & Cap Rates 🏢

> **Ultra-fast, zero-browser LoopNet commercial real estate scraper.** Extract office buildings, industrial warehouses, retail plazas, multi-family assets, asking prices, price per sqft ($/SF), Cap Rates (%), occupancy rates, and listing broker contacts across the US on **256MB RAM**.

***

### ⚡ Why Use Fast LoopNet Scraper?

Commercial Real Estate (CRE) is the highest-value real estate asset class in the world, with single transactions routinely exceeding **$5M to $100M+**. Commercial brokers, REITs, private equity syndicates, and corporate tenants pay top-tier subscription rates ($1.50 - $2.50+ per 1k records) to source off-market deals and underwriting comps.

This Actor reverse-engineers the best features of `memo23/loopnet-scraper-ppe` (531 users, 38.5K runs) and `memo23/apify-loopnet-search-cheerio` while running **without expensive proxy unblocker bloat or headless browser overhead**.

```mermaid
graph LR
    A[Location & Property Filters] --> B[Fast LoopNet Scraper]
    B --> C[Asking Prices & Price / SF]
    B --> D[Cap Rates % & Building Sq Ft]
    B --> E[Tenancy, Year Built & Occupancy]
    B --> F[Broker Contact & Advisory Firm]
    B --> G[Clean JSON / CSV Dataset]
```

***

### 🚀 Key Features

| Commercial Field | Description | Example |
|---|---|---|
| **Property Details** | Title, full address, city, state, postal code, listing URL | `Brickell Financial Centre, 1111 Brickell Ave, Miami FL` |
| **Financial Valuation** | Asking price ($) and Price per Square Foot ($/SF) | `$38,500,000 ($642 / SF)` |
| **Investment Metrics** | Capitalization Rate (%) and tenant occupancy % | `Cap Rate: 6.4%, Occupancy: 96.2%` |
| **Building Specs** | Gross building area (Sq Ft), property classification | `60,000 SF Class A Office Tower` |
| **Tenancy Structure** | Single-Tenant NNN or Multi-Tenant leased | `Multi-Tenant` |
| **Listing Brokerage** | Broker name, advisory firm (CBRE, JLL, Colliers), phone | `David C. Higgins, CBRE, +1 305-374-1000` |

***

### 📥 Input Parameters

```json
{
  "locations": [
    "Miami, FL",
    "Austin, TX"
  ],
  "transactionType": "for-sale",
  "propertyType": "office",
  "minPrice": 5000000,
  "maxPrice": 50000000,
  "minCapRate": 6.0,
  "maxItems": 30
}
```

***

### 📤 Sample Output (JSON)

```json
{
  "propertyTitle": "Brickell Financial Centre — Class A Office Tower",
  "address": "1111 Brickell Ave",
  "city": "Miami",
  "state": "FL",
  "postalCode": "33131",
  "listingUrl": "https://www.loopnet.com/Listing/1111-Brickell-Ave-Miami-FL/29184710/",
  "price": "$38,500,000",
  "priceNumeric": 38500000,
  "pricePerSqFt": "$642 / SF",
  "buildingSizeSqFt": 60000,
  "capRatePercent": 6.4,
  "propertyType": "Office",
  "transactionType": "For Sale",
  "yearBuilt": 2017,
  "tenancyType": "Multi-Tenant",
  "occupancyPercent": 96.2,
  "brokerName": "David C. Higgins",
  "brokerCompany": "CBRE Commercial Capital Markets",
  "brokerPhone": "+1 305-374-1000",
  "imageUrl": "https://images1.loopnet.com/i2/brickell-financial-centre-office.jpg",
  "scrapedAt": "2026-10-22T18:00:00.000Z"
}
```

***

### 💼 Business Use Cases

- **Private Equity & REIT Deal Sourcing**: Pipeline institutional commercial properties meeting minimum Cap Rate hurdles.
- **Underwriting & Appraisals**: Calculate accurate price per square foot comp averages across major metropolitan markets.
- **Tenant Representation**: Track available industrial warehouses and Class A offices for corporate relocation.
- **Broker Networking & Co-Brokerage**: Build targeted phone lists of listing brokers at CBRE, JLL, Colliers, and Marcus & Millichap.

***

### 🛡️ Integration Ready

Directly export results to **Google Sheets, Airtable, Notion, Webhooks, Make.com, Zapier**, or download via CSV/JSON.
Runs on standard 256MB/512MB RAM for minimal Apify compute unit costs.

# Actor input Schema

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

US cities or states to search commercial listings for (e.g. 'Miami, FL', 'Dallas, TX', 'Austin, TX', 'Atlanta, GA').

## `startUrls` (type: `array`):

Direct LoopNet search result URLs (e.g. 'https://www.loopnet.com/search/commercial-real-estate/miami-fl/for-sale/').

## `transactionType` (type: `string`):

Commercial deal type: 'for-sale' or 'for-lease'.

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

Category of commercial asset.

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

Total number of commercial property listings to extract.

## `minPrice` (type: `integer`):

Minimum asking price filter.

## `maxPrice` (type: `integer`):

Maximum asking price filter.

## `minCapRate` (type: `number`):

Minimum Capitalization Rate (e.g. 5.5, 7.0).

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

Apify Proxy or custom residential proxies. Residential proxies are recommended for CoStar/LoopNet.

## Actor input object example

```json
{
  "locations": [
    "Miami, FL",
    "Austin, TX"
  ],
  "startUrls": [],
  "transactionType": "for-sale",
  "propertyType": "all",
  "maxItems": 30,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `results` (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 = {
    "locations": [
        "Miami, FL",
        "Austin, TX"
    ],
    "startUrls": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("rbbscrap/fast-loopnet-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": [
        "Miami, FL",
        "Austin, TX",
    ],
    "startUrls": [],
}

# Run the Actor and wait for it to finish
run = client.actor("rbbscrap/fast-loopnet-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": [
    "Miami, FL",
    "Austin, TX"
  ],
  "startUrls": []
}' |
apify call rbbscrap/fast-loopnet-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rbbscrap/fast-loopnet-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/JNLgicmJng9WHtW6g/builds/IqEH0HOmSVjDcZk8N/openapi.json