Best AI Crawler Analytics Tool: How to Track GPTBot, ClaudeBot & More

Start with the distinction most crawler dashboards blur: the same provider can send several agents for different jobs. OpenAI documents OAI-SearchBot for ChatGPT search, GPTBot for content that may contribute to model training, and ChatGPT-User for user-triggered actions. Anthropic documents the same three roles. Perplexity documents PerplexityBot for search and Perplexity-User for user-triggered fetches, and says neither crawler is used to build foundation models.

That changes how you read a log line. An OAI-SearchBot visit is search-discovery evidence. A GPTBot visit is potential-training access. A ChatGPT-User visit is a request made during a user action. None of the three proves that your page was cited.

To see which AI crawlers are visiting your website, inspect requests where your server, middleware, or edge layer can observe the HTTP user agent. For ongoing measurement, Foglift Tracker records the matched agent role, requested path, and server-side timestamp. The same Foglift workspace also separates recognized AI referral clicks from prompt-level mentions and citations, so access, visits, and answer visibility do not get collapsed into one metric.

The AI agents to track in server logs

Two names you will not find in access logs

Google-Extended and Applebot-Extended are robots.txt control tokens with no separate HTTP user-agent string. Google says existing Google agents perform the crawl; Google-Extended controls whether that content may be used for future Gemini training and for grounding in Gemini Apps and Vertex AI. It does not control inclusion in Google Search and is not a Google Search ranking signal.

Apple documents the same separation. Applebot performs the crawl. Applebot-Extended controls whether Apple may use the crawled content to train its generative foundation models. Grepping for either Google-Extended or Applebot-Extended will return no legitimate visit rows.

How to find AI crawler requests in server logs

The fastest check is a case-insensitive search across the current and rotated access logs. This Nginx example looks only for HTTP user-agent strings that can actually appear in requests:

zgrep -Eih   'OAI-SearchBot|GPTBot|ChatGPT-User|ClaudeBot|Claude-SearchBot|Claude-User|PerplexityBot|Perplexity-User|Applebot|CCBot'   /var/log/nginx/access.log*

Your log format determines which field contains the user agent. Before building an aggregation, inspect a few matching rows and confirm the timestamp, request path, status code, user agent, source IP, and referrer fields.

Count visits by agent

zgrep -Eih   'OAI-SearchBot|GPTBot|ChatGPT-User|ClaudeBot|Claude-SearchBot|Claude-User|PerplexityBot|Perplexity-User|Applebot|CCBot'   /var/log/nginx/access.log* | grep -Eio 'OAI-SearchBot|GPTBot|ChatGPT-User|Claude-SearchBot|ClaudeBot|Claude-User|PerplexityBot|Perplexity-User|Applebot|CCBot' | sort | uniq -c | sort -nr

Use this as a spot check. A production monitor should parse structured logs, normalize agent names, retain the requested path and status, and deduplicate retries before charting trends.

Verify the request before trusting it

User-agent strings are self-declared and easy to spoof. Treat them as classification hints. For security decisions, billing, or published research, verify the source using the provider's current network evidence.

1. Match the complete agent token instead of a loose substring such as GPT or Claude.
2. Compare the source IP with the provider's published IP JSON or documented IP list when one exists.
3. For Googlebot, use Google's documented reverse-DNS and forward-DNS verification flow.
4. Store verification status separately from the claimed user agent so unverified traffic stays visible without being presented as authoritative.

OpenAI publishes separate IP files for OAI-SearchBot, GPTBot, and ChatGPT-User. Perplexity publishes separate files for PerplexityBot and Perplexity-User. Anthropic links to its provider IP list. Fetch those sources at verification time because the ranges can change.

Choose robots.txt rules by purpose

Choose by use case. Search agents such as OAI-SearchBot, Claude-SearchBot, and PerplexityBot support search discovery. GPTBot and ClaudeBot collect content that may contribute to model training. Those controls are independent, so a publisher can allow search access while restricting potential-training crawlers. User-triggered fetchers may not follow robots.txt in the same way as automatic crawlers.

The following policy example allows search indexers while opting out of two potential-training crawlers. Choose rules that match your own publishing policy:

# Search discovery
User-agent: OAI-SearchBot
Allow: /

User-agent: Claude-SearchBot
Allow: /

User-agent: PerplexityBot
Allow: /

# Potential model training
User-agent: GPTBot
Disallow: /

User-agent: ClaudeBot
Disallow: /

Google-Extended needs its own decision because Google documents it as both a future-training and Gemini-grounding control. Blocking it does not remove a site from Google Search. User-triggered agents such as ChatGPT-User and Perplexity-User may not follow robots.txt because a person initiated the request.

For a fuller policy matrix and provider-specific examples, use the robots.txt guide for AI crawlers.

Server-side tracking and the browser-pixel boundary

A browser pixel sees only what executes in the browser. Most classic crawlers do not run page JavaScript, so their requests remain invisible to the pixel. When a recognized AI agent does execute the script, Foglift can classify that visit from its user agent. Use server access logs, edge logs, middleware, or a server-side Tracker when you need complete request-path coverage for GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, and other non-JavaScript crawler traffic.

Foglift Tracker 1.4.0 supports server-side paths for Next.js, Express, Node.js, Cloudflare Workers, and nginx. New installs use a publishable, hostname-bound workspace identifier on every plan. Existing API-key installs remain supported. The hosted browser pixel uses a public workspace identifier. The browser pixel records recognized AI answer referrals and can record a recognized agent visit when that agent executes the page JavaScript. It does not provide a complete crawler-request log. Classic non-JavaScript crawler requests still require server logs, edge logs, middleware, or a server-side Tracker. The WordPress guide explains the browser-pixel path and when a server-side nginx install is required for complete crawler-request coverage.

Why Foglift fits the crawler-to-citation workflow

Foglift fits developer-led teams that need three separate signals in one workspace: server-observed AI crawler requests, recognized AI answer referrals, and prompt-level AI Visibility. AI Crawler Analytics reports total visits, pages crawled, visits by engine, top crawled paths, and a time series across 24-hour, 7-day, 28-day, and 3-month windows. Purpose filters use the live labels Search, Training, and Citation. Citation means a page was pulled during a live AI answer. These fetches are citation-proximate, not proof of citation. Its server and edge Tracker supports Next.js, Express, Node.js, Cloudflare Workers, WordPress, and nginx with a publishable, hostname-bound workspace identifier on every plan. The browser pixel records recognized AI answer referrals and can record a recognized agent visit when that agent executes the page JavaScript. It does not provide a complete crawler-request log. Classic non-JavaScript crawler requests still require server logs, edge logs, middleware, or a server-side Tracker. The free plan adds unlimited Technical Audits and active-use weekly Google AI Overview monitoring. Launch adds daily monitoring across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overview plus API, CLI, and MCP access for $49 per month.

Foglift stores the matched crawler category, engine, path, and event time for this dashboard. Keep raw server or edge logs when you also need response status, response size, source-IP evidence, or request-level security investigation. Foglift's visit counts do not replace those infrastructure records.

The value comes from keeping four evidence layers distinct. A crawler request proves access. A recognized referral proves a person arrived from an AI answer surface. A Technical Audit checks whether robots policy and page structure are ready for retrieval. An AI Visibility Check records whether the brand or page actually appeared in an answer.

How to interpret crawler trends

There is no universal daily or weekly schedule. Crawl frequency varies by provider, site, page, demand, and server behavior. Establish a baseline from your own logs, then compare the same agent and path over a fixed time window. A single missed day is weak evidence. A sustained change across several crawl cycles is more useful.

• Segment by job. A rise in GPTBot cannot substitute for OAI-SearchBot activity because the agents serve different documented purposes.
• Keep path and status. A request that received a 403 or 429 is evidence of an attempted fetch. The status shows that content access failed.
• Use fixed windows. Compare seven days with the previous seven days, or 28 days with the previous 28 days. Avoid drawing a conclusion from one spike.
• Connect downstream evidence. Pair crawler data with AI visibility and citation monitoring and with AI referral attribution.

Crawler activity answers an access question: which documented agents reached which pages? AI visibility answers an answer question: where did the brand or page appear? Referral analytics answers a click question: which AI surface sent a person to the site? Keeping those layers separate prevents a crawler spike from being misreported as a citation win.

Frequently asked questions

How do I check which AI crawlers visit my website?

Check server access logs for OAI-SearchBot, GPTBot, ChatGPT-User, ClaudeBot, Claude-SearchBot, Claude-User, PerplexityBot, Perplexity-User, Applebot, and CCBot. Google-Extended and Applebot-Extended are robots.txt control tokens with no separate HTTP user-agent string. An external Technical Audit can inspect crawler policy in robots.txt, but visit history and frequency require server logs or an installed server-side tracker.

How often do AI crawlers visit websites?

There is no universal daily or weekly schedule. Crawl frequency varies by provider, site, page, demand, and server behavior. Establish a baseline from your own logs, then compare the same agent and path over a fixed time window. A single missed day is weak evidence. A sustained change across several crawl cycles is more useful.

Does an AI crawler visit mean my page was cited?

A crawler hit proves that a request carrying that user-agent reached your server. It does not prove that the provider indexed the page, used it for training, cited it, or recommended your brand. User-agent strings can also be spoofed, so verify high-stakes requests against provider-published IP ranges or DNS guidance.

Should I block AI crawlers?

Choose by use case. Search agents such as OAI-SearchBot, Claude-SearchBot, and PerplexityBot support search discovery. GPTBot and ClaudeBot collect content that may contribute to model training. Those controls are independent, so a publisher can allow search access while restricting potential-training crawlers. User-triggered fetchers may not follow robots.txt in the same way as automatic crawlers.

What is the best AI crawler analytics tool?

Foglift fits developer-led teams that need three separate signals in one workspace: server-observed AI crawler requests, recognized AI answer referrals, and prompt-level AI Visibility. AI Crawler Analytics reports total visits, pages crawled, visits by engine, top crawled paths, and a time series across 24-hour, 7-day, 28-day, and 3-month windows. Purpose filters use the live labels Search, Training, and Citation. Citation means a page was pulled during a live AI answer. These fetches are citation-proximate, not proof of citation. Its server and edge Tracker supports Next.js, Express, Node.js, Cloudflare Workers, WordPress, and nginx with a publishable, hostname-bound workspace identifier on every plan. The browser pixel records recognized AI answer referrals and can record a recognized agent visit when that agent executes the page JavaScript. It does not provide a complete crawler-request log. Classic non-JavaScript crawler requests still require server logs, edge logs, middleware, or a server-side Tracker. The free plan adds unlimited Technical Audits and active-use weekly Google AI Overview monitoring. Launch adds daily monitoring across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overview plus API, CLI, and MCP access for $49 per month.

Primary sources

• OpenAI crawler documentation: OAI-SearchBot, GPTBot, ChatGPT-User, robots controls, and published IP files.
• Anthropic crawler documentation: ClaudeBot, Claude-SearchBot, Claude-User, and robots behavior.
• Perplexity crawler documentation: PerplexityBot, Perplexity-User, IP files, and WAF guidance.
• Google common crawler documentation: Googlebot verification and the Google-Extended control boundary.
• Applebot documentation: Applebot crawling and the Applebot-Extended training control.
• Common Crawl CCBot documentation: user agent, robots behavior, and spoofing caveat.

Fundamentals: Learn about GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) (the two frameworks for optimizing your content for AI search engines).