# The Artifact Machine Accessibility Audit (`artifact-machine/artifact-machine-accessibility-audit`) Actor

Check WCAG accessibility issues using axe-core in a real browser.

- **URL**: https://apify.com/artifact-machine/artifact-machine-accessibility-audit.md
- **Developed by:** [The Artifact Machine](https://apify.com/artifact-machine) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / accessibility audit report

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/platform/actors/running/actors-in-store#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

## The Artifact Machine Accessibility Audit

This Actor checks one public webpage for common accessibility issues using a bounded Playwright browser run and axe-core rules.

It is built for site owners, agencies, QA teams, and launch teams that need a compact WCAG-oriented signal before a deeper manual accessibility review.

### Input

- `url`: public page URL to audit.
- `includeIssueSamples`: include compact selector and HTML snippets for top issues.
- `navigationTimeoutSecs`: page navigation timeout, capped at 60 seconds.

### Output

The Actor writes one dataset item with:

- normalized URL and final browser URL
- score and letter grade
- issue counts by severity
- compact issue list
- axe run counts and page title

### Limits

This is not a legal compliance certification. It is an automated page-level screen for issues that axe-core can detect. Keyboard workflows, account-only pages, checkout flows, PDFs, media transcripts, and design intent still need human review.

### Pricing Hypothesis

Start at `$2.00` to `$5.00` per completed page-level accessibility report after private cloud runtime cost is measured.

# Actor input Schema

## `url` (type: `string`):

The public webpage to audit. If no scheme is provided, https:// is assumed.

## `includeIssueSamples` (type: `boolean`):

Include compact selector and HTML snippets for the top accessibility issues.

## `navigationTimeoutSecs` (type: `integer`):

Maximum page navigation time in seconds.

## Actor input object example

```json
{
  "url": "https://example.com",
  "includeIssueSamples": true,
  "navigationTimeoutSecs": 30
}
```

# Actor output Schema

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

Default dataset items. Each item contains the target URL, score, grade, issue counts, axe run counts, and actionable accessibility issues.

## `summary` (type: `string`):

The same single-run summary stored as the OUTPUT key-value record.

# 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 = {
    "url": "https://example.com"
};

// Run the Actor and wait for it to finish
const run = await client.actor("artifact-machine/artifact-machine-accessibility-audit").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 = { "url": "https://example.com" }

# Run the Actor and wait for it to finish
run = client.actor("artifact-machine/artifact-machine-accessibility-audit").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "url": "https://example.com"
}' |
apify call artifact-machine/artifact-machine-accessibility-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=artifact-machine/artifact-machine-accessibility-audit",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/ucLMdTA9sd8X8ZIh3/builds/J1jEebyK0VVMfxLTV/openapi.json