crawlie, developed by Spronta, is a local site crawler focused on technical SEO and Generative Engine Optimization audits. The tool runs automated checks across more than 40 SEO and GEO rules and produces plain-English guidance plus machine-readable reports for triage and tracking. It emits Health, GEO, and Accessibility scores and supports terminal, JSON, CSV, and shareable HTML outputs, with cross-platform CLI options for automation. Digital marketers, SEO specialists, and developers use it to prepare sites for search and AI discovery.

What tasks can you actually use it for?

The tool performs technical scans for broken links, redirects, and missing metadata and runs checks aimed at AI-search visibility, labeled GEO. Crawlie audits more than 40 distinct checks, and each flagged item includes a plain-English explanation of the problem and suggested fixes. That makes it suitable for issue triage, prioritizing remediation, and producing reproducible lists that a developer or SEO can action during a site sprint.

How detailed and assessable are the reports?

Reporting provides three separate scores: Health for traditional SEO, GEO for AI-readiness, and Accessibility aligned to WCAG. Outputs are available as human-readable terminal text and as machine formats for tracking. Report formats include JSON, CSV, and self-contained HTML, which helps hand off findings to issue trackers or analytics pipelines without manual transcription. Score separation supports targeted remediation by discipline.

What inputs and environments does it accept?

The tool runs as a command-line utility installable via npm, and it is also offered as a native macOS .dmg. Crawlie respects a site’s robots.txt and can seed crawls from sitemap.xml files, which helps avoid unwanted indexing. Its CLI focus supports scripting and continuous-integration workflows, letting teams embed audits into automated QA stages or nightly jobs.

Does it fit into AI-driven auditing workflows?

Crawlie includes a built-in Model Context Protocol server so AI assistants can browse and run audits directly against a live site, enabling agent-driven analysis. The tool uses a local-first execution model, keeping processing local to the machine to reduce external data exposure and shorten turnaround for iterative scans. That design supports workflows where agents, developer scripts, or human reviewers need rapid, reproducible site snapshots.

A practical, open-source choice for teams that value transparent tooling

Crawlie is a practical option for SEO and marketing teams that prefer open-source tooling under the MIT license and need machine-friendly outputs for automation. Expect its guidance to accelerate triage, but plan manual verification of fixes for critical pages. The project’s agent-first approach and positive reception in developer and SEO circles make it worth evaluating where reproducible audits and local execution matter.