Goal: crawl a documentation site (a few hundred pages, JavaScript-rendered navigation), get clean Markdown per page, feed it to an indexing pipeline. Two tracked projects do this and I cannot tell from the READMEs which is the smaller operational commitment.
Crawl4AI presents as a Python library: pip install crawl4ai, a setup command that installs Playwright browsers, then an AsyncWebCrawler that returns Markdown per page. Apache-2.0 with an attribution request in the README.
Firecrawl presents as a hosted API first, with a self-host option. The repository has an API service, a Playwright service and Redis, as a docker compose stack. AGPL-3.0, and the README notes the self-hosted version lacks some features of the cloud one.
Questions: for a few hundred pages run once a week, is Crawl4AI's "library in your own script" model enough, or do you end up rebuilding the queueing that Firecrawl's stack gives you? And has anyone compared the Markdown quality on the same site? The comparison page here /compare/crawl4ai-vs-firecrawl covers features; I am after the operational side.