Scrapling integrated as OpenClaw's scraping backbone
Scrapling, an open-source scraping library, has been integrated into OpenClaw as its core scraping backbone. This addresses common issues with AI agents struggling with real-world web data, broken scrapers, Cloudflare walls, and selectors that fail when sites update.
Key features and capabilities
Unlike most scraping tools that rely on hardcoded selectors that break when websites redesign, Scrapling learns the structure of a page and adjusts automatically when things change without requiring code rewrites.
- 774x faster than BeautifulSoup with Lxml
- Works across HTTP and full browser automation
- Supports CSS, XPath, text, and regex selectors
- Async sessions for parallel scraping
- Includes a CLI so non-developers can use it without writing code
Getting started
Installation is straightforward:
pip install "scrapling[ai]"The library is fully open source under a BSD-3 license and has been gaining traction on GitHub.
📖 Read the full source: r/openclaw
👀 See Also
Self-Maintaining Documentation System Using Fenced Blocks for Zero Drift
A developer built a bash script that extracts structured data directly from source files and injects it into CLAUDE.md through fenced HTML comment blocks, ensuring documentation stays in sync with code without manual maintenance.
Cowork vs. Claude Chat: Document Extraction Accuracy Comparison
A developer tested Claude.ai chat and Cowork on extracting data from 140+ page financial PDFs using identical prompts. Chat produced institutional-grade results with self-correction and zero errors across 150+ data points, while Cowork fabricated reconciling line items, reversed unit counts, and had prior-year column contamination.
Multi-Agent Career Mentor Built with Ollama and MCP for Local AI
A developer built a 5-agent AI system that analyzes resumes and generates career intelligence reports using Ollama with llama3 locally. The system chains agent outputs so each builds on previous context, with MCP handling tool integration.
Rivet Actors adds SQLite storage: one database per agent, tenant, or document
Rivet Actors now supports SQLite storage where each actor gets its own SQLite database, enabling millions of independent databases for AI agents, multi-tenant SaaS, collaborative documents, or per-user isolation.