# LeadScraper (`cdubiel/lead-scraper`) Actor

Scrape a list of urls and receive business contact information, social media links, and a description of the services.

This actor will scrape across multiple pages in the sitemap and returns a confidence score to every phone number and email that it finds.

webscraper, scrape leads, web scraper

- **URL**: https://apify.com/cdubiel/lead-scraper.md
- **Developed by:** [Claire Dubiel](https://apify.com/cdubiel) (community)
- **Categories:** Lead generation, AI, Automation
- **Stats:** 146 total users, 1 monthly users, 100.0% runs succeeded, 9 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

$2.30 / 1,000 runs

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/platform/actors/running/actors-in-store#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

## Service Company Website Scraper

An Apify actor that scrapes service company websites and extracts structured information about the business, including contact information, services offered, hours of operation, and more.

### Features

- Extracts company name, description, and contact information
- Identifies services offered by the company
- Extracts business hours, social media links, and reviews
- Finds pricing information and FAQs
- Handles multiple URLs in a single run
- Supports SSL verification options
- Optional Cloudflare bypass capability

### Input

The actor accepts the following input parameters:

- `urls` - An array of service company website URLs to scrape (required)
- `verifySSL` - Whether to verify SSL certificates (default: `true`)
- `bypassCloudflare` - Whether to attempt to bypass Cloudflare protection (default: `true`)
- `metadata` - Optional custom metadata to include with each result

Example input:

```json
{
  "urls": [
    "https://www.example1.com/",
    "https://www.example2.com/"
  ],
  "verifySSL": true,
  "bypassCloudflare": true,
  "metadata": {
    "project_id": "example-project",
    "source": "manual",
    "category": "roofing"
  }
}
```

### Output

The actor outputs a JSON object for each URL containing the following information:

- `url` - The URL of the scraped website
- `title` - The title of the website
- `meta_description` - The meta description of the website
- `main_content` - The main content of the website
- `contact_information` - Contact information extracted from the website
  - `phones` - List of phone numbers with confidence scores
  - `main_phone` - The main phone number with highest confidence
  - `emails` - List of email addresses with confidence scores
  - `main_email` - The main email address with highest confidence
  - `address` - The physical address of the business
- `services` - List of services offered by the company
- `hours_of_operation` - Business hours by day of the week
- `social_media_links` - Links to social media profiles
- `reviews` - Customer reviews found on the website
- `pricing` - Pricing information for services
- `faqs` - Frequently asked questions
- `success` - Whether the scraping was successful
- `error` - Error message if scraping failed

### Example Usage

````javascript
const Apify = require('apify');

Apify.main(async () => {
    const input = {
        urls: [
            "https://www.example1.com/",
            "https://www.example2.com/"
        ],
        verifySSL: true,
        bypassCloudflare: true,
        metadata: {
            project_id: "example-project",
            source: "manual",
            category: "roofing"
        }
    };
    
    // Run the actor and wait for it to finish
    const run = await Apify.call('your-username/service-company-scraper', input);
    
    // Print the results
    const dataset = await Apify.openDataset(run.defaultDatasetId);
    const { items } = await dataset.getData();
    console.log('Results:', items);
});

### Development

#### Project Structure

- `main.py` - Entry point for the Apify actor
- `scraper.py` - Contains the `ServiceCompanyScraper` class
- `requirements.txt` - Python dependencies
- `INPUT_SCHEMA.json` - Input schema for the Apify actor
- `OUTPUT_SCHEMA.json` - Output schema for the Apify actor
- `Dockerfile` - Docker configuration for the Apify actor

#### Adding New Features

To add new extraction capabilities:

1. Add a new method to the `ServiceCompanyScraper` class in `scraper.py`
2. Call the method from the `scrape` method
3. Update the output schema if necessary

# Actor input Schema

## `urls` (type: `array`):

List of service company website URLs to scrape
## `metadata` (type: `object`):

Optional custom metadata to include with each result. This can be any valid JSON object.
## `verifySSL` (type: `boolean`):

Whether to verify SSL certificates
## `bypassCloudflare` (type: `boolean`):

Whether to attempt to bypass Cloudflare protection

## Actor input object example

```json
{
  "urls": [
    "https://www.example1.com/",
    "https://www.example2.com"
  ],
  "metadata": {
    "project_id": "example-project",
    "source": "manual",
    "category": "roofing",
    "tags": [
      "service",
      "construction"
    ]
  },
  "verifySSL": true,
  "bypassCloudflare": true
}
````

# 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 = {
    "urls": [
        "https://www.example1.com/",
        "https://www.example2.com"
    ],
    "metadata": {
        "project_id": "example-project",
        "source": "manual",
        "category": "roofing",
        "tags": [
            "service",
            "construction"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("cdubiel/lead-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 = {
    "urls": [
        "https://www.example1.com/",
        "https://www.example2.com",
    ],
    "metadata": {
        "project_id": "example-project",
        "source": "manual",
        "category": "roofing",
        "tags": [
            "service",
            "construction",
        ],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("cdubiel/lead-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "urls": [
    "https://www.example1.com/",
    "https://www.example2.com"
  ],
  "metadata": {
    "project_id": "example-project",
    "source": "manual",
    "category": "roofing",
    "tags": [
      "service",
      "construction"
    ]
  }
}' |
apify call cdubiel/lead-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=cdubiel/lead-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/WaiUqIdg4ShZ1q3PJ/builds/IUwgU4rqLVGHJd11e/openapi.json