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Description
BrowserQL serves as a specialized scraping language and browser automation solution designed to effectively navigate bot detection systems while leaving minimal traces of automation. It features inherent anti-detection capabilities that require no configuration, enabling users to circumvent services like Cloudflare and Datadome without the need for additional plugins or setups. Additionally, BrowserQL can seamlessly handle common CAPTCHA challenges, even those embedded within iframes or shadow DOMs, utilizing techniques such as auto-humanized clicking, scrolling, and typing patterns, as well as hidden debugging protocols and automatic fingerprint evasion, all complemented by residential proxy integration for a more authentic browsing experience. In contrast to traditional DIY setups utilizing Playwright, which demand the use of stealth plugins and frequent manual interventions for mouse or keyboard simulations, BrowserQL provides a more efficient and streamlined process that significantly reduces the chances of detection by automation libraries. This allows users to focus on their scraping tasks without the constant worry of being flagged or blocked by sophisticated bot detection mechanisms.
Description
Yozh Scraper is an advanced open-source toolkit designed for web scraping and crawling, optimized for extensive data extraction tasks. Utilizing Playwright, Python, and Redis, it adeptly navigates intricate JavaScript-rendered websites while effectively circumventing contemporary anti-bot measures.
Highlighted Features:
• Anti-Detection Scraping: Utilizes Camoufox along with genuine Chrome instances to disguise browser fingerprints, successfully navigating stringent anti-scraping mechanisms.
• Dual Microservices Architecture: Offers an asynchronous Scraper API for rendering pages, combined with an Open Crawler that features SSE streaming, site-mapping, and deduplication capabilities.
• Native MCP Integration: Seamlessly connects with AI agents such as Claude Code/Desktop, LangChain, and n8n through built-in Model Context Protocol (/mcp) endpoints.
• Intelligent Parsing & Configurations: Comes pre-set for popular platforms like Amazon, Google, LinkedIn, and others, with optional self-healing parsing powered by LLMs.
• Scalable Enterprise Solutions: Supports horizontal scaling through Docker Compose, accommodates various proxy types (Residential/Mobile/Data Center), and includes a user-friendly web interface for testing purposes.
• This toolkit is ideal for developers looking to streamline their data extraction processes while maintaining compliance with anti-bot regulations.
API Access
Has API
Yes
API Access
Has API
No
Screenshots View All
No images available
Integrations
AgentKit
Yes
Browserless
Yes
Claude
Yes
Claude Desktop
Yes
Cursor
Yes
CyberYozh
No
Google Chrome
Yes
LangChain
Yes
Make
Yes
Model Context Protocol (MCP)
Yes
Integrations
AgentKit
No
Browserless
No
Claude
No
Claude Desktop
No
Cursor
No
CyberYozh
Yes
Google Chrome
No
LangChain
No
Make
No
Model Context Protocol (MCP)
No
Pricing Details
$25 per month
Free Trial
No
Free Version
Yes
Pricing Details
$0
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Browserless
Country
United States
Website
www.browserless.io/feature/browserql-browser-automation-tool
Vendor Details
Company Name
CyberYozh
Founded
2014
Country
Serbia
Website
data.cyberyozh.pro/