What AI Crawlers Should I Allow Access? Complete Guide for 2025

Understanding AI Crawlers and Their Purpose

AI crawlers are automated bots that request and collect content from websites to serve different purposes in the artificial intelligence ecosystem. Unlike traditional search engine crawlers that primarily index content for search results, AI crawlers operate across three distinct categories, each with different implications for your website’s visibility and content protection. Understanding these categories is essential for making informed decisions about which crawlers to allow or block in your robots.txt file.

The first category consists of training crawlers that collect web content to build datasets for large language model development. These crawlers, such as GPTBot and ClaudeBot, systematically gather information that becomes part of an AI model’s knowledge base. Once your content enters a training dataset, it can be used to generate responses without users ever visiting your original website. According to recent data, training crawlers account for approximately 80% of all AI crawler traffic, making them the most aggressive category in terms of bandwidth consumption and content collection.

The second category includes search and citation crawlers that index content for AI-powered search experiences and answer generation. These crawlers, like OAI-SearchBot and PerplexityBot, help surface relevant sources when users ask questions in ChatGPT or Perplexity. Unlike training crawlers, search crawlers may actually send referral traffic back to publishers through citations and links in AI-generated responses. This category represents a potential opportunity for visibility in emerging AI-powered discovery channels that are becoming increasingly important for website traffic.

The third category comprises user-triggered fetchers that activate only when users specifically request content through AI assistants. When someone pastes a URL into ChatGPT or asks Perplexity to analyze a specific page, these fetchers retrieve the content on demand. These crawlers operate at significantly lower volumes and are not used for model training, making them less of a concern for content protection while still providing value for user-initiated interactions.

Major AI Crawlers and Their User Agents

OpenAI operates three primary crawlers with distinct functions within the ChatGPT ecosystem. GPTBot is the main training crawler that collects data specifically for model training purposes, and blocking this crawler prevents your content from being incorporated into future GPT model versions. OAI-SearchBot handles real-time retrieval for ChatGPT’s search features and does not collect training data, making it valuable for maintaining visibility in ChatGPT search results. ChatGPT-User activates when users specifically request content, making one-off visits rather than systematic crawls, and OpenAI confirms that content accessed via this agent is not used for training.

Anthropic’s crawler strategy includes ClaudeBot as the primary training data collector and Claude-User for user-triggered fetching. The company has faced criticism for its crawl-to-refer ratio, which Cloudflare data indicates ranges from 38,000:1 to over 70,000:1 depending on the time period. This means Anthropic crawls significantly more content than it refers back to publishers, making it a primary target for blocking if content protection is your priority.

Google’s approach uses Google-Extended as a specific token controlling whether Googlebot-crawled content can be used for Gemini AI training. This is important because blocking Google-Extended may affect your visibility in Gemini’s “Grounding with Google Search” feature, potentially reducing citations in AI-generated responses. However, AI Overviews in Google Search follow standard Googlebot rules, so blocking Google-Extended does not impact regular search indexing.

Perplexity’s dual-crawler system includes PerplexityBot for building the search engine database and Perplexity-User for user-triggered visits. Perplexity publishes official IP ranges for both crawlers, allowing webmasters to verify legitimate requests and prevent spoofed user agents from bypassing restrictions.

Configuring Your Robots.txt File

The most straightforward way to manage AI crawler access is through your robots.txt file, which provides directives that tell crawlers what they can and cannot access. Each User-agent line identifies which crawler the rules apply to, and the Allow or Disallow directives that follow specify what content that bot can access. Without a directive following a User-agent declaration, the bot won’t know what to do and may default to allowing access.

For publishers who want to block all training crawlers while allowing search and citation crawlers, a balanced approach works well. This configuration blocks GPTBot, ClaudeBot, anthropic-ai, Google-Extended, Meta-ExternalAgent, and other training crawlers while allowing OAI-SearchBot, PerplexityBot, and user-triggered fetchers. This strategy protects your content from being incorporated into AI models while maintaining visibility in AI-powered search and discovery platforms.

# Block AI Training Crawlers
User-agent: GPTBot
Disallow: /

User-agent: ClaudeBot
Disallow: /

User-agent: anthropic-ai
Disallow: /

User-agent: Google-Extended
Disallow: /

User-agent: Meta-ExternalAgent
Disallow: /

# Allow AI Search Crawlers
User-agent: OAI-SearchBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: Perplexity-User
Allow: /

For publishers seeking maximum protection, a comprehensive configuration blocks all known AI crawlers. This approach prevents any AI platform from accessing your content, whether for training or search purposes. However, this strategy comes with trade-offs: you lose visibility in emerging AI-powered discovery channels, and you may miss referral traffic from AI search results.

You can also implement path-specific rules that allow different access levels for different sections of your website. For example, you might allow training crawlers to access your public blog content while blocking them from accessing private sections or sensitive information. This granular approach provides flexibility for publishers who want to balance content protection with AI visibility.

Beyond Robots.txt: Stronger Protection Methods

While robots.txt provides a starting point for managing AI crawler access, it relies on crawlers voluntarily respecting your directives. Some crawlers don’t respect robots.txt, and bad actors can spoof user agent strings to bypass restrictions. Publishers seeking stronger protection should consider additional technical measures that operate independently of crawler compliance.

IP verification and firewall rules represent the most reliable method for controlling AI crawler access. Major AI companies publish official IP address ranges that you can use to verify legitimate crawlers. OpenAI publishes IP ranges for GPTBot, OAI-SearchBot, and ChatGPT-User at openai.com/gptbot.json, openai.com/searchbot.json, and openai.com/chatgpt-user.json respectively. Amazon provides IP addresses for Amazonbot at developer.amazon.com/amazonbot/ip-addresses/. By allowlisting verified IPs in your firewall while blocking requests from unverified sources claiming to be AI crawlers, you prevent spoofed user agents from bypassing your restrictions.

Server-level blocking with .htaccess provides another layer of protection that operates independently of robots.txt compliance. For Apache servers, you can implement rules that return a 403 Forbidden response to matching user agents, regardless of whether the crawler respects robots.txt. This approach ensures that even crawlers that ignore robots.txt directives cannot access your content.

Web Application Firewall (WAF) configuration through services like Cloudflare allows you to create sophisticated rules combining user agent matching with IP address verification. You can set up rules that allow requests only when both the user agent matches a known crawler AND the request comes from an officially published IP address. This dual verification approach prevents spoofed requests while allowing legitimate crawler traffic.

HTML meta tags provide page-level control for certain crawlers. Amazon and some other crawlers respect the noarchive directive, which tells crawlers not to use the page for model training while potentially allowing other indexing activities. You can add this to your page headers: <meta name="robots" content="noarchive">.

The Trade-offs of Blocking AI Crawlers

Deciding whether to block AI crawlers isn’t straightforward because each decision involves significant trade-offs that affect your website’s visibility and traffic. Visibility in AI-powered discovery is increasingly important as users shift from traditional search to AI-powered answer engines. When users ask ChatGPT, Perplexity, or Google’s AI features about topics relevant to your content, they may receive citations to your website. Blocking search crawlers could reduce your visibility in these emerging discovery platforms, potentially costing you traffic as AI search becomes more prevalent.

Server load and bandwidth costs represent another important consideration. AI crawlers can generate significant server load, with some infrastructure projects reporting that blocking AI crawlers reduced their bandwidth consumption from 800GB to 200GB daily, saving approximately $1,500 per month. High-traffic publishers may see meaningful cost reductions from selective blocking, making the decision economically justified.

The core tension remains: training crawlers consume your content to build models that may reduce users’ need to visit your site, while search crawlers index content for AI-powered search that may or may not send traffic back. Publishers must decide which trade-offs align with their business model. Content creators and publishers who rely on direct traffic and ad revenue may prioritize blocking training crawlers. Publishers who benefit from being cited in AI responses may prioritize allowing search crawlers.

Verifying Crawlers Are Respecting Your Blocks

Setting up robots.txt is only the beginning of managing AI crawler access. You need visibility into whether crawlers are actually respecting your directives and whether fake crawlers are attempting to bypass your restrictions. Checking server logs reveals exactly which crawlers are accessing your site and what they’re requesting. Your server logs typically live in /var/log/apache2/access.log for Apache servers or /var/log/nginx/access.log for Nginx. You can filter for AI crawler patterns using grep commands to identify which bots are hitting your content pages.

If you see requests from blocked crawlers still hitting your content pages, they may not be respecting robots.txt. This is where server-level blocking or firewall rules become necessary. You can run this command on your Nginx or Apache logs to see which AI crawlers have been hitting your website:

grep -Ei "gptbot|oai-searchbot|chatgpt-user|claudebot|perplexitybot|google-extended|bingbot" access.log | awk '{print $1,$4,$7,$12}' | head

Fake crawlers can spoof legitimate user agents to bypass restrictions and scrape content aggressively. Anyone can impersonate ClaudeBot from their laptop and initiate crawl requests using standard command-line tools. The most reliable verification method is checking the request IP against officially declared IP ranges. If the IP matches an official list, you can allow the request; otherwise, block it. This approach prevents spoofed requests while allowing legitimate crawler traffic.

Analytics and monitoring tools increasingly differentiate bot traffic from human visitors. Cloudflare Radar tracks AI bot traffic patterns globally and provides insights into which crawlers are most active. For site-specific monitoring, watch for unexpected traffic patterns that might indicate crawler activity. AI crawlers often exhibit bursty behavior, making many requests in short periods before going quiet, which differs from the steady traffic you’d expect from human visitors.

Maintaining Your Crawler Blocklist

The AI crawler landscape evolves rapidly with new crawlers emerging regularly and existing crawlers updating their user agents. Maintaining an effective AI blocker strategy requires ongoing attention to catch new crawlers and changes to existing ones. Check your server logs regularly for user agent strings containing “bot,” “crawler,” “spider,” or company names like “GPT,” “Claude,” or “Perplexity.” The ai.robots.txt project on GitHub maintains a community-updated list of known AI crawlers and user agents that you can reference.

Review your crawl analytics at least quarterly to identify new crawlers hitting your properties. Tools like Cloudflare Radar provide visibility into AI crawler traffic patterns and can help identify new bots. Test your implementations regularly by verifying that your robots.txt and server-level blocks are working by checking crawler access in your analytics. New crawlers appear frequently, so schedule regular reviews of your blocklist to catch additions and ensure your configuration remains current.

Emerging crawlers to watch include browser-based AI agents from companies like xAI (Grok), Mistral, and others. These agents may use user agent strings like GrokBot, xAI-Grok, or MistralAI-User. Some AI browser agents, like OpenAI’s Operator and similar products, don’t use distinctive user agents and appear as standard Chrome traffic, making them impossible to block through traditional methods. This represents an emerging challenge for publishers seeking to control AI access to their content.