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Having an AI agent find your products is just the beginning. The real goal is making sure that discovery leads to a completed sale.

A shopper’s AI assistant can read your catalog, compare your products, and decide yours is the best match, but none of that will turn into a sale if the agent can’t confirm the item is in stock, check whether it ships in time, and complete the purchase. 

With a few steps, your store can be ready for AI-powered shopping. The industry is settling on a small set of protocols that let agents find products, check stock, confirm shipping, and complete a purchase. No need to be a developer — you only need to know what each protocol does for your store and what to put in place so you’re ready when it arrives.

Here, we’ll walk through how to close the gap between discovery and conversion so you can get agentic commerce sales on your terms.

It helps to treat each protocol as another sales channel rather than a competing standard you have to bet on. For example, you already accept Visa, Mastercard, and American Express without choosing between them; each one reaches a different set of customers. AI protocols work the same way. 

Supporting one puts you in front of shoppers in one place, and supporting another reaches shoppers in another. Neither of them asks you to pick a winner.

That matters because these protocols fall into two groups, and only one of them is something shoppers touch today.

Two of these work under the hood, connecting AI to how your store runs. The others are the channels that put your products in front of shoppers. Here’s what each one does and where it stands today.

Woo is responsible for building the behind-the-scenes pieces, so all you have to do there is stay on a current version and keep your data clean. Woo is rolling out these protocols to select groups of merchants, so stay tuned for more news about access and merchant requirements.

The key is keeping your store’s data accurate and up to date. When an agent answers a shopper, it’s making a promise on your behalf, so the information behind that promise has to be right. Five steps get you there.

Update your stock count in real time. This is important for both agents and customers. If it tells a shopper something is available when it actually sold out that morning, your store is left to honor a promise it can’t keep. Your stock should report in real time, from one reliable source.

Put shipping and return details on your product pages. Keep delivery estimates, shipping options, and return terms where the product data lives. Agents need to be able to quickly find answers to customer questions like, s “can I get this by Friday?” or “what’s the return window?”

Set up Stripe for WooCommerce only once — it’s your route to ACP. With Stripe’s Agentic Commerce Suite, one implementation is all it takes to find and buy your products across different AI assistants (like Copilot or Gemini). Shoppers purchase products with the AI assistant, but they’re still your customers. Stripe takes care of payments and fraud protection, and you keep your catalog, your customers, and control of your store. One caveat: this works through the Stripe extension specifically, so stores running WooPayments (which is powered by Stripe) can’t use it yet. 

Send your product feed to Google Merchant Center. The Google for WooCommerce extension does this for you. A clean Merchant Center feed is the groundwork for UCP and for showing up across Google’s AI shopping tools, including Gemini and AI Mode in Search. Set it up now, and you’re ready as UCP matures, instead of catching up later.

Check your data every quarter. AI visibility is something you need to keep an eye on. Each quarter, look up your products in ChatGPT, Gemini, and Perplexity, both by name and the way a shopper would describe them. Wherever your data shows up wrong, out of date, or missing, fix it. Stores that regularly update their data will see the most success.

Woo is also testing OpenAI’s Product Feed Spec and other new standards to help you stay ahead of this. Stores with clean, well-organized product data pick up each one faster, because the hard part is already done. The Agentic Commerce Hub is the place to follow as new features ship.

All of this is only as good as the platform it sits on. On a closed platform, you depend on that vendor’s decisions about which protocols to support and when. If they don’t build for a given AI platform, your store sits out of that channel until they do, and you have no say in the timing.

Because WooCommerce is open source, your store works with open standards and can adopt new protocols quickly, without waiting on a single company’s timeline. You connect your catalog once and reach shoppers through whatever agent they use, rather than rebuilding for each new platform that comes along.

• Check how often your inventory syncs. If it updates on a daily schedule, look into real-time options before agents start checking your stock.
• Open one of your best-selling product pages and check that shipping estimates and return terms are right there in the product data, not only written up on a separate policy page.
• If you haven’t connected Stripe for WooCommerce, install it and look at the path to the Agentic Commerce Suite. If you have, check that you’re on the waitlist for the agent features.
• Sync your catalog to Google Merchant Center through Google for WooCommerce if you haven’t already.

Picture a specialty outdoor gear store running on WooCommerce. Its inventory reports in real time, every product page carries shipping and return terms, and its catalog flows to both the Stripe Agentic Commerce Suite and Google Merchant Center. A shopper asks an AI assistant to put together a three-season backpacking setup that ships within a week and stays under budget. The agent checks live stock, confirms the delivery window from the store’s shipping data, and recommends the tent, pack, and layers as a set. The customer can then make the purchase right in the assistant or complete the transaction on the merchant’s site.

The agent will pass over a competing store that only updates inventory overnight, keeps its shipping terms on a separate policy page, and can’t make those guarantees. Even though you have similar products, the outcome is different because your store is ready.

About

Lindsey Peacock

Lindsey is a Toronto-based writer, editor, and American expat who helps businesses grow with her background in ecommerce and technology.

The post From found to bought: Getting your store ready to sell through AI  appeared first on MASSIVE News.

AI crawlers can consume bandwidth, increase server load, and collect your content without sending visitors back to your website. Blocking them isn’t as simple as adding a few lines to robots.txt, since not every crawler respects those instructions.

You also need to distinguish between different types of AI bots.

• Training crawlers such as GPTBot, ClaudeBot, and Bytespider collect content for AI development.
• User-triggered agents, such as ChatGPT-User and Perplexity-User, may help your pages appear as cited sources in AI-generated answers.

Blocking every AI-related user agent could reduce your visibility as well as your server traffic.

This guide explains how to control AI crawler access without accidentally blocking legitimate search engines or useful AI referral traffic. You will learn how to:

• Identify the AI crawlers you may want to block
• Set rules in robots.txt
• block requests at the NGINX server level
• Configure Cloudflare’s AI crawler controls
• Test your rules and confirm they work

By the end, you will have a layered approach that gives you greater control over who can access your content and how much server capacity automated crawlers consume.

Why robots.txt Alone Won’t Stop AI Crawlers

AI-related crawlers serve several different purposes. Some collect content for model training, while others build search indexes or retrieve pages in response to a user request. High-volume crawling can consume bandwidth and server resources, but the impact depends on the crawler, its request rate, your caching configuration, and your application stack.

This is exactly why you should identify the crawler and its purpose before deciding whether to block it.

While adding a disallow directive to your robots.txt file is the traditional method for managing bots, it is ineffective against these bots because it runs on an honor system. Aggressive scrapers, poorly configured rogue bots, and many proprietary data brokers routinely ignore robots.txt entirely.

If you want to protect your infrastructure and intellectual property, you need to implement server-level blocking using NGINX or implement other firewall measures. This allows you to intercept these unauthorized requests at the server level, where you can drop the connection by returning a 403 Forbidden response before the request ever reaches your web application or consumes your server’s computing resources.

Suggested read: How To Use ModSecurity and OWASP CRS For Web App Firewall (WAF) To Secure Your Website

Which AI Bots Should You Block in 2026?

If you want to protect your server resources and intellectual property, you should prioritize blocking the following primary training crawlers.

Targeting High-Volume AI Training Crawlers

The following control tokens and user agents are associated primarily with AI training, model development, or large-scale dataset collection:

• GPTBot
• ClaudeBot
• Bytespider
• Amazonbot
• Applebot-Extended
• Google-Extended
• Meta-ExternalAgent
• CCBot

Claude-SearchBot should be considered separately, as Anthropic uses it to support search results rather than for general model training. 

PerplexityBot is also separate from bulk training crawlers. Perplexity states that it uses PerplexityBot to build its search index and surface links in Perplexity results, not to train foundation models. Blocking it may prevent your pages from appearing in Perplexity search results. 

Evaluating Real-Time AI Search Agents

Real-time fetchers operate under a different set of rules than bulk scrapers. Instead of indiscriminately harvesting data, these digital assistants visit your server only when a human query explicitly triggers them to fetch your content. This makes them an important component for maintaining visibility in modern, AI-driven search results.

Integrating with these tools can be a good marketing move, but it requires balancing visibility against your specific privacy concerns.

• ChatGPT-User
• Perplexity-User
• OAI-SearchBot
• Claude-User

Allowing these agents enables AI services to retrieve and cite your current content in response to user requests. It doesn’t guarantee that your page will be selected, cited, ranked prominently, or visited by the user. However, if your domain contains sensitive data or strictly paywalled content, you should weigh your goals carefully. If you prefer total privacy over AI search exposure, block these alongside the bulk training bots.

Anthropic uses separate user agents for different purposes. ClaudeBot crawls content for model development, Claude-SearchBot supports Claude’s search results, and Claude-User may retrieve a page in response to an individual user’s request. 

Suggested read: How to Use Cloudflare Firewall Rules to Protect Your Web Application

Will Blocking AI Crawlers Hurt Your Google Rankings?

Blocking AI crawlers won’t harm your traditional Google Search rankings if you implement your security blocks correctly and target the right bots. Google designed its ecosystem to allow web admins to opt out of generative AI training without sacrificing their organic SEO visibility.

Google uses the Googlebot user agents to crawl, index, and rank your pages in standard search engine results. For AI training and generative model grounding (such as feeding live search context to Gemini), Google uses a separate control token known as Google-Extended. Disallowing Google-Extended tells Google not to use your content for training and grounding in certain Gemini systems. Google states that Google-Extended doesn’t affect inclusion or ranking in Google Search.

Google-Extended doesn’t control AI features that form part of Google Search itself. Access to those features is governed through Googlebot and standard Search controls such as nosnippet, data-nosnippet, max-snippet, and noindex.

However, there is a massive technical caveat for web admins: unlike most web scrapers, Google-Extended doesn’t have its own separate HTTP request user-agent string. The physical crawling is still executed using standard Google crawler user agents, meaning the Google-Extended token functions purely in a control capacity within your robots.txt file.

Because the phrase “Google-Extended” will never appear in your server’s incoming HTTP requests, you can’t block it at the NGINX or Cloudflare WAF level using a simple User-Agent string match. You must use the traditional robots.txt opt-out method for Google’s AI training and rely on server-level blocks for other companies’ bots.

Because of this shared infrastructure, you must be extremely cautious when writing your NGINX rules or WAF policies. Using broad wildcards like *Google* or *bot* to stop scrapers will result in a catastrophic SEO failure, as you will accidentally block the legitimate Googlebot, Googlebot-Image, and Googlebot-Video indexers that your business relies on.

Suggested read: Linux Server Hardening: 11 Steps to Secure a Production VPS 

Implementing a Multi-Layered Strategy for AI Bot Management

Relying on a single method for blocking unwanted AI traffic can leave your infrastructure exposed. If you want to build a truly resilient defense, it is best to implement a layered strategy that covers public directives, server-level interception, and network-edge filtering. This ensures that if one mechanism fails or is ignored, your subsequent layers act as a fail-safe to protect your server resources.

Layer 1 – Block AI Bots with robots.txt

To set up your first layer of defense, create or edit a simple text file named robots.txt and place it in the root directory of your website (usually the public_html or htdocs folder). 

To edit your robots.txt, you can simply open your web host’s file manager, create this file, and copy-paste the code below to ask all major 2026 AI training bots to stay away from your entire site:

User-agent: GPTBot
User-agent: ClaudeBot
User-agent: Bytespider
User-agent: Amazonbot
User-agent: Applebot-Extended
User-agent: Google-Extended
User-agent: Meta-ExternalAgent
User-agent: CCBot
Disallow: /

Why robots.txt alone is not enough (RFC 9309 is advisory)

While adding a robots.txt file is the industry standard first step, it is important to understand that it operates entirely on an honor system. RFC 9309 standardizes how crawlers should interpret robots.txt, but it doesn’t provide authentication or access control. Compliant crawlers follow its directives voluntarily, while another client can still request the same URL directly. 

Reputable companies like Google and OpenAI currently program their bots to respect these rules, but aggressive scrapers, rogue data brokers, and malicious AI crawlers will completely ignore your robots.txt file and scrape your content anyway. Therefore, relying on this file alone leaves your server vulnerable to heavy automated traffic, so you must implement server-level blocking as well.

Layer 2 – Block AI Bots at the NGINX Layer

If you search for tutorials on how to block bots using NGINX, almost every old guide will tell you to place an if statement directly inside your server block (for example, if ($http_user_agent ~* "GPTBot") { return 403; }).

Complex rewrite logic inside an NGINX if block can produce unexpected results, particularly when it is placed inside a location block. A simple condition that performs only a return is much less problematic.

If you want to block traffic, you should use the map directive, which is a better and highly optimized alternative to if statements. When a visitor sends a request, NGINX checks their User-Agent exactly once against this map and assigns a variable (like a simple true/false flag). Because it is evaluated outside the complex location rules, it is incredibly fast and can automatically apply to every single website hosted on your entire server without repeating code.

To implement this on your server, you will need to access your global NGINX configuration (often located in /etc/nginx/conf.d/) and create a new file named ai_bot_map.conf. Paste the following map directive into that file, which flags the 2026 AI bots with a 1 (true) if they match, and a 0 (false) for normal human visitors:

map $http_user_agent $is_ai_bot {
    default 0;
    "~*GPTBot" 1;
    "~*ClaudeBot" 1;
    "~*Bytespider" 1;
    "~*Amazonbot" 1;
    "~*Meta-ExternalAgent" 1;
    "~*CCBot" 1;
}

Don’t add Google-Extended or Applebot-Extended to this map. They are robots.txt control tokens rather than independent crawler User-Agent strings. Instead, use robots.txt to control them. 

Choosing the response code

After identifying the crawlers, you need to decide how your server should handle them when they arrive. Here is a list of appropriate HTTP status codes you can return when rejecting a web request.

403 Forbidden 

Returning a 403 Forbidden status is the most common and standard choice because it clearly communicates to the bot that the server understood the request but is actively refusing to fulfill it. 

444 (Nginx-specific, drops the connection with no response)

If you are dealing with an incredibly aggressive bot that is hitting your server thousands of times a minute and draining your bandwidth, you should use NGINX’s special 444 response code. Unlike standard HTTP codes, 444 doesn’t send any headers or error pages to the bot; it simply closes the connection immediately. This can reduce the response work and outbound data associated with rejected requests, although NGINX must still accept and process the connection far enough to match the rule. 

410 Gone (signals permanent removal, deters re-crawls)

Another good option is to return a 410 Gone status code, which signals to the AI crawler that the resource it is looking for has been permanently deleted and won’t be returned. Use 410 Gone only when the requested resource has been permanently removed. Don’t return 410 solely as a bot-blocking technique for pages that remain available to other visitors. Use 403 or 444 when you are refusing access based on the requester rather than the state of the resource. 

Logging Blocked Requests for Audit

You shouldn’t blindly block traffic without keeping a record of what your server is doing. You can instruct NGINX to log blocked bot attempts to a separate file so they don’t clutter your main website analytics.

By adding a simple directive like access_log /var/log/nginx/blocked_ai_bots.log; inside the block that returns your 403 or 444 code, you create an isolated, easily readable audit trail where you can safely monitor which AI companies are trying to harvest your data.

Suggested read: How to Block IP Address Using WordPress .htaccess File to Stop Bad Visitors

Layer 3 – Block AI Bots at the Edge with Cloudflare WAF

If you manage your DNS through Cloudflare, you can easily intercept AI bots at the network edge before they ever reach your web server by configuring their built-in bot policies. Cloudflare has updated its approach to AI traffic by introducing new features that categorize bots into three distinct behaviors:

• “Search” (crawlers indexing content to answer queries later and drive referrals)
• “Agent” (real-time automated bots acting on a human’s behalf, like chat fetch bots) 
• “Training” (scrapers permanently absorbing your data to train large language models).

Configure AI Bot Policies

Cloudflare provides two related ways to manage AI traffic:

In AI Crawl Control, open the Crawlers tab to review individual crawlers and set each one to Allow or Block.

For broader behavior-based controls, open the Security settings and configure how Cloudflare handles Search, Agent, and Training traffic. Each category can be allowed, blocked across the domain, or blocked only on pages where Cloudflare detects advertising.

For each type of bot, you can choose to “Block (on all pages),” “Allow (do not block),” or select “Block on pages with ads,” which uses Cloudflare’s automated detection to block bots strictly on monetized pages while leaving the rest of your site accessible.

Additionally, from September 15, 2026, Cloudflare will automatically block ‘Training’ and ‘Agent’ bots on pages with ads for all new domains, while keeping Search bots allowed. Cloudflare’s updated system will apply the most restrictive rule to multi-purpose crawlers, such as Googlebot or Applebot, that crawl for both search indexing and AI training.

From 15 September 2026, Cloudflare plans to evaluate multi-purpose crawlers against all their declared behaviors. A crawler that combines Search and Training may therefore be affected by your Training rule even when Search traffic is allowed.

Review Cloudflare’s displayed outcome before applying category-wide rules, particularly where a crawler also supports conventional search discovery.

Before enforcing broad blocks across your entire domain, you can also establish governance rules using Cloudflare’s AI Audit tools. The AI Audit dashboard provides visibility into which AI services are scanning your website, allowing you to clearly see the volume of requests from specific bots and understand how they interact with your content.

By analyzing this traffic, novice users can make data-driven security decisions, such as explicitly allowing search-focused tools that drive referral traffic, while firmly rejecting exploitative scrapers.

Future of AI Content Monetization

Cloudflare is also testing Pay Per Crawl, which is currently in closed beta. Participating site owners can set a price and choose whether to allow, block, or charge supported crawlers.

A crawler that doesn’t provide the required payment information receives an HTTP 402 Payment Required response. Availability and crawler participation remain limited, so this shouldn’t yet be treated as a general replacement for blocking.

Suggested read: What is Fail2Ban with Setup & Configuration? (Detailed Guide)

Verify that NGINX Blocking is Working

After deploying your NGINX mapping rules, you shouldn’t simply assume they are functioning perfectly. Server-level configurations are powerful but unforgiving; a minor syntax error could potentially block legitimate traffic or fail to stop the unwanted bots you are targeting.

You need to validate your setup to ensure your defenses are correct and not causing collateral damage to your site’s availability. Follow the steps below to verify that your block list is successfully intercepting requests.

Curl with a faked GPTBot User-Agent and expect 403

The easiest way for a novice to test if their server block is working is to pretend to be an AI bot using the command line. Open your computer’s terminal (or Command Prompt) and type the following command exactly:

curl -I -A "GPTBot/1.0" https://example.com

This command sends a fake request to your site claiming to be GPTBot; if your NGINX rules are working correctly, your terminal will print out an HTTP/2 403 Forbidden error (or return an empty reply if you used the 444 code), proving the block is active.

Tail NGINX access logs and grep for the bot user-agents

To watch your server actively defend itself in real-time, you can filter your live server logs for specific bot names. Log in to your server via SSH and run the command:

tail -f /var/log/nginx/access.log | grep -i "gptbot"

The tail -f command streams the log file live, while grep filters out everything except requests containing the word “gptbot”, allowing you to sit back and watch the exact moment the AI crawler hits your server and gets rejected.

Cross-check with Cloudflare bot analytics

Finally, you can verify your edge-level blocks by reviewing your visual data within the Cloudflare dashboard. Navigate to Security and then click on Events to see a complete log of all web traffic that triggered your WAF rules.

By filtering this list by “User Agent” or specifically looking at the “Block AI bots” rule metrics, you can visually confirm how many thousands of requests from scrapers like ClaudeBot and Bytespider were successfully dropped by Cloudflare’s network before they ever touched your origin server.

Final Thoughts: Take Control of Your Server Traffic

In this article, we have discussed how to manage custom NGINX configurations and protect your websites. It might sound overwhelming, but RunCloud makes the entire process effortless.

With RunCloud, you can easily manage and deploy sites on your own cloud infrastructure without needing to be a command-line expert. Its highly intuitive dashboard allows you to make quick NGINX updates and instantly reload your server to deploy those security rules across all your hosted applications in just a few clicks.

Whether you’re hosting a single high-traffic web application or managing dozens of client sites, having complete, frictionless control over your hosting environment is important. 

Start using RunCloud today.

Should You Block AI Crawlers? Common Questions Answered

The post How to Block AI Crawlers (GPTBot, ClaudeBot, PerplexityBot, Bytespider) on Your Server in 2026 appeared first on MASSIVE News.