# AI Website & PDF Extractor — RAG JSON (`pagelytix/pagelytix`) Actor

Extract structured, AI-ready JSON from websites and PDFs including clean text, metadata, schema, DOM elements, semantic sections, links, social media links, and chunks for LLMs, RAG pipelines, embeddings, and semantic search.

- **URL**: https://apify.com/pagelytix/pagelytix.md
- **Developed by:** [Pagelytix](https://apify.com/pagelytix) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 results

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?

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

## AI Website & PDF Extractor — RAG-Ready JSON

### 🚀 What this Actor does

Turns any webpage or PDF into structured, AI-ready JSON for LLMs, RAG, and embeddings in one call.

### One-line description

Extract clean text, metadata, structured webpage elements, schema, and AI-ready semantic chunks from public webpages and PDFs using one consistent JSON format.

***

### Overview

Analyze public webpages and PDFs and return structured, AI-ready JSON. Extract clean text, metadata, structured DOM elements, schema, semantic sections, and AI-ready chunks for LLMs, RAG, embeddings, vector databases, semantic search, and website intelligence.

***

### Features

- Extract clean text from webpages and PDFs
- Metadata extraction (title, emails, phones, addresses)
- Structured DOM extraction (webpages)
- JSON-LD schema extraction (when available)
- Internal and external link extraction
- Social media link extraction
- CTA detection (buttons, contact links)
- Automatic semantic section detection
- AI-ready chunk generation
- Page statistics
- Consistent JSON structure across webpages and PDFs

***

### Output Structure

```text
data
├── url
├── meta
├── schema
├── stats
├── dom
└── text
    ├── raw
    ├── clean
    ├── sections
    └── chunks
```

### Field Descriptions

- **url** – Final processed URL after redirects
- **meta** – Metadata (title, emails, phones, addresses)
- **schema** – JSON-LD structured data
- **stats** – Word count, headings, links, images, reading time
- **dom** – Structured elements (headings, images, links, social links, CTAs)
- **text** – Raw text, cleaned text, semantic sections, AI-ready chunks

Perfect For

- LLM applications
- Retrieval-Augmented Generation (RAG)
- Vector databases
- Embedding pipelines
- AI chatbots
- Knowledge bases
- Semantic search
- Website intelligence
- Content indexing
- Document ingestion

***

Why this Actor?

Most scrapers return raw HTML or inconsistent JSON. This Actor normalizes webpages and PDFs into one consistent AI-ready structure optimized for LLMs, RAG pipelines, embeddings, vector databases, and semantic search.

Input Example

```json
{
  "urls": [
    "https://example.com",
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
  ]
}
```

Output Example

```json
{
  "url": "...",
  "meta": {},
  "schema": [],
  "stats": {},
  "dom": {
    "headings": [],
    "images": [],
    "internalLinks": [],
    "externalLinks": [],
    "social": [],
    "cta": []
  },
  "text": {
    "raw": "",
    "clean": "",
    "sections": [],
    "chunks": []
  }
}
```

# Actor input Schema

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

Webpages or PDFs to extract

## Actor input object example

```json
{
  "urls": [
    "https://example.com"
  ]
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("pagelytix/pagelytix").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("pagelytix/pagelytix").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 '{}' |
apify call pagelytix/pagelytix --silent --output-dataset

```

## MCP server setup

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

```

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/hGULoafhyxl7ueHYY/builds/6QG8hECF4CZIIGH6H/openapi.json