Facebook Scraper

The problem

Manual data collection from Facebook is blocked by aggressive anti-bot measures, rate limits, and complex browser fingerprinting. Scraping pages and groups at scale typically requires expensive API keys or constant maintenance of custom scripts that break frequently.

What it does

• Discovers Facebook pages and public groups based on specific geographic locations and business categories.
• Extracts detailed metadata including follower counts, engagement stats, contact info, and localized addresses.
• Executes full browser simulation using Playwright with stealth scripts to mimic human behavior.
• Exports structured data in JSON and CSV formats while automatically downloading profile and cover images.
• Manages session persistence with support for residential proxy rotation and interrupted scrape resumption.

Frameworks & tools

Python, Playwright, Chromium, and Google Custom Search API (optional for discovery).

Why this beats prompting it yourself

Writing a prompt to scrape Facebook fails because LLMs cannot handle browser-level anti-detection or session management. This skill provides a production-ready execution layer with built-in deduplication, automated filtering of private groups, and a pre-configured proxy manager that handles the heavy lifting of social media automation.

Use cases

• Lead generation for local businesses by scraping niche-specific Facebook pages in target cities.
• Market research and sentiment analysis by monitoring public community groups for specific industries.
• Building local business directories with verified contact information and physical addresses.
• Competitor tracking to monitor engagement levels and post frequency across different page tiers.

Known limitations

Requires Python 3 and Chromium installed. Private groups and deactivated profiles are automatically skipped. Residential proxies are highly recommended for large-scale operations.