# Shopify AI Readiness Scanner - AI SEO & llms.txt Audit (`rationalistic_candle_ucn/shopify-ai-readiness-scanner`) Actor

Audit any Shopify storefront for AI search: what ChatGPT, Perplexity and Claude can read. Checks robots.txt for GPTBot, OAI-SearchBot and PerplexityBot, product JSON-LD, llms.txt, sitemap and the agent-commerce endpoint. A 0-100 score, an A-F grade and a fix per check.

- **URL**: https://apify.com/rationalistic\_candle\_ucn/shopify-ai-readiness-scanner.md
- **Developed by:** [Bruce McGinley](https://apify.com/rationalistic_candle_ucn) (community)
- **Categories:** E-commerce, SEO tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $40.00 / 1,000 store scanneds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Shopify AI Readiness Scanner

Score any Shopify storefront on what AI shopping assistants can actually read from it. ChatGPT, Perplexity, Claude and Google's shopping agents recommend products they can fetch and parse; a store that blocks their crawlers, ships no product structured data, or hides its catalogue behind JavaScript is invisible to them however good its products are. This Actor runs the same checks an assistant's crawler would hit, grades the store from A to F, and returns every check with its status and the fix.

### How it works

Give it a list of storefront URLs or domains. For each one the Actor fetches the homepage, `robots.txt`, `llms.txt` and the sitemap, locates a product page, and evaluates:

- **AI crawler access.** Whether the major AI shopping crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, OAI-SearchBot and others) are allowed to reach product pages, and which robots.txt rule blocks each one that is not.
- **Product structured data.** Whether product pages carry `Product` and `Offer` JSON-LD with price, availability and identifiers an assistant can quote.
- **Readable without JavaScript.** Whether the homepage and product page contain real content before any script runs, since most AI crawlers do not run JavaScript.
- **llms.txt and sitemap.** Whether the store publishes the files assistants use to find and prioritise pages.
- **Agent-commerce endpoint.** Whether the store's agent-facing catalogue endpoint answers, and whether its filters actually filter.

Each store becomes one dataset item with a score out of 100, a letter grade, counts of passed, warned and failed checks, the list of AI crawlers the store blocks, and the full list of checks with a plain-language explanation and a concrete fix for each.

### Tutorial

1. Open the Actor and paste storefront domains into **Stores**, one per line. `example.com`, `www.example.com` and `https://example.com/` all work.
2. Click **Start**. A store takes a few seconds; a list of fifty takes about five minutes because the scanner is paced to be polite to the stores it reads.
3. Open the **Output** tab, or export the dataset as JSON, CSV or Excel. Sort by `score` to find the stores with the most to fix, or filter on `failed` greater than zero.

Any public storefront can be scanned. Stores on platforms other than Shopify get the same checks, with the platform-specific fixes left generic.

### Pricing

This Actor uses pay-per-event pricing. You are charged one **store-scan** event for every store that returns a report. A store that could not be scanned, because it is offline, behind a bot challenge, or mistyped, still gets a row in the dataset explaining why, and is not charged. You can cap spend on any run with the maximum total charge setting; the Actor stops cleanly when it is reached and says how many stores were left. There is no charge for the run itself beyond the platform's own compute.

On the Apify free plan you can run the Actor within the free monthly usage allowance; the scanner also caps fresh scans at roughly twelve per minute per run, which the Actor respects automatically.

### Input example

```json
{
  "stores": ["allbirds.com", "gymshark.com", "https://www.bombas.com/"]
}
```

### Output example

One item per store:

```json
{
  "store": "allbirds.com",
  "origin": "https://www.allbirds.com",
  "platform": "shopify",
  "score": 82,
  "grade": "B",
  "provisional": false,
  "scannedAt": "2026-09-03T14:02:11.000Z",
  "passed": 6,
  "warnings": 2,
  "failed": 1,
  "blockedCrawlers": ["Google-Extended"],
  "checks": [
    {
      "id": "ai-crawlers",
      "title": "AI shopping crawler access",
      "status": "warn",
      "severity": "medium",
      "detail": "1 of 12 AI crawlers are blocked from your product pages by robots.txt.",
      "fix": "Remove the Disallow rule for Google-Extended, or add an explicit Allow for /products/."
    }
  ],
  "error": null
}
```

### Use cases

- **Agencies** auditing a client list before a pitch, or re-running it monthly to show progress.
- **Merchants** checking their own store and a handful of competitors.
- **Researchers and journalists** measuring how much of a category is readable by AI assistants.
- **AI agents** that need a structured readiness score for a store as one step in a longer workflow; the dataset is plain JSON and every field is documented here.

### Related Actors

Pair this with a Shopify products scraper to compare what a store sells with what an assistant can see of it, or with a website content crawler to read the pages this Actor flags.

### FAQ

**Does it need any login or API key?** No. It reads only public pages and public files.

**Is the store told it was scanned?** The scanner identifies itself with a named user agent and honours robots.txt. A store that disallows it is reported as such and not scored.

**Why is a score marked provisional?** When a product page could not be found, the structured-data checks could not run and the score covers fewer checks.

**How current is a result?** A store scanned recently by anyone is served from a short-lived cache; otherwise it is scanned fresh at the time of the run.

**Something looks wrong.** Open an issue on the Actor's Issues tab with the store domain and the check in question.

# Actor input Schema

## `stores` (type: `array`):

Storefront URLs or domains, one per line. Any public storefront can be scanned; Shopify stores get the fullest report. Each store scanned is one billable event.

## Actor input object example

```json
{
  "stores": [
    "allbirds.com",
    "gymshark.com"
  ]
}
```

# Actor output Schema

## `reports` (type: `string`):

One item per store: score, grade, every check with its status and fix, and the AI crawlers the store blocks.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "stores": [
        "allbirds.com",
        "gymshark.com"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("rationalistic_candle_ucn/shopify-ai-readiness-scanner").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "stores": [
        "allbirds.com",
        "gymshark.com",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("rationalistic_candle_ucn/shopify-ai-readiness-scanner").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "stores": [
    "allbirds.com",
    "gymshark.com"
  ]
}' |
apify call rationalistic_candle_ucn/shopify-ai-readiness-scanner --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rationalistic_candle_ucn/shopify-ai-readiness-scanner"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/4Am0guPNyES2VFn13/builds/dhRfpLOwpJtthRZet/openapi.json