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Documentation Index

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Open SourceApplications Layer

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Scrapling

Adaptive Python scraping that survives website redesigns — selectors relocate themselves after layout changes, with stealth mode for anti-bot resistance.
Scrapling GitHub

Type

Open Source (BSD-3)

Stack Layer

Applications

Language

Python

Stars

48k+

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What it is

Scrapling is a Python web scraping framework that handles the full spectrum from simple HTTP requests to anti-bot-resistant browser automation. Its headline feature is adaptive element tracking: scraped selectors automatically relocate themselves when a website redesigns, dramatically reducing maintenance overhead for long-running scraping projects. It matches Parsel and Scrapy for performance on text extraction while adding stealth browsing modes and Cloudflare bypass for modern dynamic sites. Concurrent crawling with pause/resume is built in, and Scrapling ships an MCP server that lets AI agents call it directly as a tool — making it a natural fit for autonomous research agents that need structured web data. Benchmarks show strong performance relative to Selenium and Playwright alternatives for data-extraction tasks.
Use this when you’re building scrapers that need to outlive website changes, or when you need anti-bot-resistant data extraction for AI pipelines — the MCP integration makes it directly usable inside agent workflows.

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Get started

GitHub ↗

Source, benchmarks, and MCP server documentation.

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