Set up proxy-aware scraping to avoid blocks on large crawl jobs using CyberYozh Data

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Turn any website into structured, MCP-ready data—automatically.

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CyberYozh Data

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CyberYozh Data is an open-source crawler and scraper that maps full websites, extracts structured JSON, and integrates natively with MCP-driven AI workflows for resilient, proxy-aware web data collection.

mcp crawlerstealth scraperllm-assisted parsingweb scrapingdata extractiondeveloper toolsai agentsopen source

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What to expect from an ideal product

1. CyberYozh Data supports rotating proxy configurations out of the box, so large crawl jobs keep running even when target sites rate-limit or block individual IP ranges.
2. The crawler maps entire website structures automatically, meaning you get full site coverage without manually listing URLs or writing custom spider logic.
3. Extracted data outputs directly as structured JSON, ready to plug into MCP-driven AI pipelines without extra parsing or transformation steps.
4. Because CyberYozh Data is open-source, teams can audit the proxy-handling code, customize retry logic, and self-host without depending on third-party scraping APIs.
5. Scraping jobs that previously failed halfway through large sites now complete reliably, thanks to built-in resilience that handles blocks, timeouts, and redirects without manual intervention.

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