anansi vs playwright-mcp
anansi: Anansi is a resilient web scraper that handles adversarial sites, survives redesigns, and improves over time. It features self-healing CSS selectors, automatic browser upgrade, TLS fingerprint mimicry, and adaptive rate limiting. It ships with an MCP server for LLM integration.; playwright-mcp: Playwright MCP is a server that leverages Playwright's browser automation capabilities to enable Large Language Models (LLMs) to interact with web pages. It utilizes structured accessibility snapshots, allowing LLMs to process web content without relying on visual input or traditional screenshots.
TL;DR
Extract structured data from product pages with adaptive selectors
- You want an agent to drive a real browser through structured accessibility snapshots instead of screenshots, so no vision model is needed.
- You need Firefox, WebKit or Edge as well as Chrome: the README's --browser option lists chrome, firefox, webkit and msedge.
- You want to test or script flows with isolated in-memory profiles (--isolated), device emulation (--device) or saved Playwright traces (--save-trace).
- Your main goal is debugging or performance analysis of a page; Chrome DevTools MCP exposes performance traces and network inspection as dedicated tools.
- You need proxies, CAPTCHA handling or large-scale scraping of protected sites; that is outside what the README claims for this server.
- You want to treat it as a sandbox: the project says its origin allow and block lists are not a security boundary.
Side-by-Side Comparison
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