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Kernel Lead Scraper Template - Google Maps

A ready-to-use lead scraper that extracts local business data from Google Maps using browser-use and the Kernel platform.

What It Does

This template creates an AI-powered web scraper that:

  1. Navigates to Google Maps
  2. Searches for businesses by type and location
  3. Scrolls through results to load more listings
  4. Extracts structured lead data (name, phone, address, website, rating, reviews)
  5. Returns clean JSON ready for your CRM or outreach tools

Quick Start

1. Install Dependencies

uv sync

2. Set Up Environment

cp .env.example .env
# Edit .env and add your OpenAI API key

3. Deploy to Kernel

kernel deploy main.py -e OPENAI_API_KEY=$OPENAI_API_KEY

4. Run the Scraper

kernel run lead-scraper scrape-leads \
  --data '{"query": "restaurants", "location": "Austin, TX", "max_results": 10}'

API Reference

Action: scrape-leads

Input Parameters:

Parameter Type Required Default Description
query string ✅ - Business type to search (e.g., "plumbers", "gyms")
location string ✅ - Geographic location (e.g., "Miami, FL")
max_results integer ❌ 20 Maximum leads to scrape (1-50)

Example Output:

{
  "leads": [
    {
      "name": "Joe's Pizza",
      "phone": "(512) 555-0123",
      "address": "123 Main St, Austin, TX 78701",
      "website": "https://joespizza.com",
      "rating": 4.5,
      "review_count": 234,
      "category": "Pizza restaurant"
    }
  ],
  "total_found": 1,
  "query": "pizza restaurants",
  "location": "Austin, TX"
}

Use Cases

  • Sales Teams: Build targeted prospect lists for cold outreach
  • Marketing Agencies: Find local businesses needing marketing services
  • Service Providers: Identify potential B2B clients in your area
  • Market Research: Analyze competitor density and ratings by location

Customization

Modify the Search Prompt

Edit the SCRAPER_PROMPT in main.py to customize what data the AI extracts:

SCRAPER_PROMPT = """
Navigate to Google Maps and search for {query} in {location}.
# Add your custom extraction instructions here
"""

Add New Fields

  1. Update BusinessLead model in models.py
  2. Modify the prompt to extract the new fields
  3. Redeploy with kernel deploy main.py

Troubleshooting

Issue Solution
No results found Try a broader search query or different location
Timeout errors Reduce max_results or check your network
Rate limiting Add delays between requests in production

Resources