Descriptions:
Fahd Mirza walks through installing and configuring Scrapling, a Python web scraping library built to solve two persistent problems for AI developers: scrapers that break when websites redesign their layouts, and anti-bot systems that block automated requests. Scrapling addresses both through intelligent element tracking that survives structural changes and a stealth fetcher that bypasses Cloudflare and similar protections by using a real browser with spoofed fingerprints via Playwright.
The core demonstration connects Scrapling’s built-in Model Context Protocol (MCP) server to a locally running 3.5 billion parameter model via Ollama, giving the AI genuine internet access without any API costs. Mirza shows the complete setup on Ubuntu — creating a Conda virtual environment, installing Scrapling and Playwright, launching the MCP server on port 8000, and running a Python script that scrapes a live website and passes the content to the Ollama model for summarization. The model successfully traverses linked pages and returns a detailed site overview.
The entire stack is free and open source. Mirza notes Scrapling’s potential for building local AI agents that need real-time web data, generating custom training datasets, and handling production scraping without extra configuration for JavaScript-heavy pages. For developers who want conversational internet access in a local LLM without paying for cloud APIs, this Scrapling plus MCP plus Ollama combination offers a practical and reproducible starting point.
📺 Source: Fahd Mirza · Published March 13, 2026
🏷️ Format: Tutorial Demo
