Check public crawler policy
Parse robots.txt for major AI search, training, classic search, common crawlers, and Content-Signal declarations at the exact URL path.
AI crawler access check
Test GPTBot, OAI-SearchBot, OAI-AdsBot, ClaudeBot, PerplexityBot, Google-Extended, robots.txt, Cloudflare Content-Signal including use levels, Applebot, Applebot-Extended, headers, meta robots, sitemap, llms.txt, and fetcher context in one transparent report.
What it checks
A crawler policy can look open while a page still blocks discovery through headers, meta tags, redirects, thin rendered content, missing AI-readable discovery files, or confusing bot roles.
Parse robots.txt for major AI search, training, classic search, common crawlers, and Content-Signal declarations at the exact URL path.
Review HTTP status, redirects, meta robots, X-Robots-Tag, canonical, readable text, and JSON-LD.
Check sitemap, llms.txt, llms-full.txt, non-standard fetcher context, and copy-ready fixes without promising guaranteed AI visibility.
Boundaries
This tool diagnoses public access signals that site owners control. It does not bypass bot defenses, log into websites, or promise citation in any AI answer surface.
Find accidental blocks that may prevent AI search or retrieval systems from reading public pages.
See which training or retrieval bots you are allowing, then choose a policy intentionally.
Every recommendation ties back to a visible rule, header, tag, status, missing file, or documented bot behavior.
Tool matrix
Start with the full AI crawler access scan, then use the focused pages when the job is llms.txt validation, technical AEO readiness, or AI search visibility prerequisites.
Tool choice
AI crawler access is one layer. Compare it with visibility tracking and llms.txt validation so teams do not treat one passing score or one Content-Signal line as a full AI search strategy.
Best for confirming whether a specific user agent is allowed or blocked at one URL path.
Best after technical blockers are fixed, when teams need prompt sampling, citations, and share-of-answer tracking.
Best for checking AI-readable discovery files, but they still need robots.txt, sitemap, metadata, and readable pages around them.
Best for separating actual crawl access, such as Applebot, from AI-use control tokens, such as Applebot-Extended.
Best for spotting search, AI input, AI training, and optional immediate/reference/full use preferences published alongside crawler rules.