# AI Search Visibility, SEO/AEO/GEO & llms.txt Audit (MCP) (`amygraphics/mena-aeo-readiness-auditor`) Actor

AI search visibility audit (AEO / GEO): score a website 0-100 on how ready it is to be cited by ChatGPT, Claude, Perplexity and Google AI — llms.txt, structured data, answer engine optimization. MCP-ready for AI agents.

- **URL**: https://apify.com/amygraphics/mena-aeo-readiness-auditor.md
- **Developed by:** [Zakaria el bouami](https://apify.com/amygraphics) (community)
- **Categories:** Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 site auditeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## AI Search Visibility, SEO/AEO/GEO & llms.txt Audit (MCP)

Your customers now ask **ChatGPT, Claude, Perplexity and Google AI** — not just Google Search. Is your website ready to be **cited by AI answer engines**?

This Actor audits any website (with a focus on Moroccan / MENA businesses) and returns an **AEO readiness score (0–100)** plus concrete recommendations.

### What it checks

- 🧬 **Structured data** — JSON-LD / schema.org, LocalBusiness markup
- 🤖 **AI-bot access** — robots.txt rules for GPTBot, ClaudeBot, PerplexityBot, Google-Extended, CCBot, Amazonbot…
- 📄 **llms.txt** — the emerging standard that helps AI assistants use your site
- 🏷️ **Meta readiness** — meta description, Open Graph, Twitter card, canonical
- 🌍 **MENA language readiness** — Arabic / French versions, hreflang
- 🗺️ **Sitemap**, single H1, viewport, HTTPS, local contact signals (tel/mailto)

### Output

One JSON record per site: score, all checks, per-bot allow/block table, detected schema types, and a prioritized recommendation list your team can execute.

### Who is it for

- 🇲🇦🇦🇪 MENA businesses & agencies preparing for AI search (AEO / GEO)
- 🌍 International AEO/SEO agencies with MENA clients (French & Arabic coverage)
- 📊 Consultants producing AI-visibility audit reports

### Use from AI agents (MCP)

This Actor is exposed as a tool through **Apify's MCP server** — any MCP client (Claude, Cursor, VS Code / Copilot, Codex, custom agents) can discover and run it without writing code:

```json
{
  "mcpServers": {
    "apify": { "url": "https://mcp.apify.com?tools=amygraphics/mena-aeo-readiness-auditor" }
  }
}
```

Then just ask: *"Use amygraphics/mena-aeo-readiness-auditor to get me this data."* Agents can also pay autonomously — this Actor is **whitelisted for agentic payments** (Direct x402 / Apify AGI prepaid token), so no Apify account is required.

### Pricing

Pay-per-event: one `site-audited` charge per successfully audited site. Unreachable sites are never charged.

***

### 🇫🇷 Version française

Vos clients demandent désormais **ChatGPT, Perplexity, Claude et les Aperçus IA de Google** — pas seulement la recherche classique. Cet Actor audite la **préparation AEO/GEO** de n'importe quel site (focus Maroc / MENA / marchés francophones) et renvoie un **score 0–100** avec recommandations prioritaires :

- 🧬 Données structurées schema.org / JSON-LD (LocalBusiness…)
- 🤖 Règles robots.txt pour **GPTBot, ClaudeBot, PerplexityBot, Google-Extended, CCBot, Amazonbot**
- 📄 Présence de **llms.txt** (standard émergent pour les assistants IA)
- 🏷️ Meta description, Open Graph, canonical, hreflang
- 🌍 Prêt pour le **FR / AR** — indispensable pour les marques présentes au Maroc et au MENA
- 🗺️ Sitemap, H1 unique, HTTPS, signaux de contact locaux

**Idéal pour :** agences GEO/AEO qui veulent automatiser leurs audits, marques francophones, entreprises actives au Maroc / MENA.

Tarification : pay-per-event — un événement `site-audited` par site audité avec succès.

***

### Agents IA (MCP)

Cet Actor est exposé comme outil du serveur **MCP d'Apify** — branchez `https://mcp.apify.com?tools=amygraphics/mena-aeo-readiness-auditor` dans Claude, Cursor, VS Code ou Codex, puis demandez vos données en langage naturel. Les agents peuvent payer seuls (x402 / AGI) : l'Actor est *whitelisted* pour les paiements agentiques.

# Actor input Schema

## `urls` (type: `array`):

One or more business website URLs to audit for AI-search (AEO/GEO) readiness.

## `chargedEventName` (type: `string`):

Pay-per-event name charged for each successfully audited site.

## Actor input object example

```json
{
  "urls": [
    "https://www.marocannonces.com"
  ],
  "chargedEventName": "site-audited"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {
    "urls": [
        "https://www.marocannonces.com"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("amygraphics/mena-aeo-readiness-auditor").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 = { "urls": ["https://www.marocannonces.com"] }

# Run the Actor and wait for it to finish
run = client.actor("amygraphics/mena-aeo-readiness-auditor").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 '{
  "urls": [
    "https://www.marocannonces.com"
  ]
}' |
apify call amygraphics/mena-aeo-readiness-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,amygraphics/mena-aeo-readiness-auditor"
        }
    }
}
```

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/e6AH428IPBkUmSNX8/builds/fxpfOHKY1xSZKJf92/openapi.json