# Apify Web To Markdown (`abdou_009/apify-web-to-markdown`) Actor

- **URL**: https://apify.com/abdou_009/apify-web-to-markdown.md
- **Developed by:** [Abdelkader BENAISSI](https://apify.com/abdou_009) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 page converteds

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Web to Markdown

Turn any web page into clean, LLM-ready **Markdown** over plain HTTP — no headless browser, no waiting. Built for **AI agents** and **RAG pipelines** that need page content as compact, structured text instead of raw HTML.

Feed it one or more URLs and get back one dataset row per page: the converted Markdown plus title, meta description, author, publish date, final URL (after redirects), HTTP status and character count.

### Why agents need this

Raw HTML is 5–10× larger than the text an LLM actually needs, and full of nav bars, cookie banners, scripts and ads. This actor extracts the **main article content** (readability, with `<article>`/`<main>` fallbacks), strips the noise, absolutizes links, and returns tight Markdown — ready to drop into a prompt, a vector store, or a dataset.

And because it's pure HTTP, a page converts in about a second — fast enough to call mid-reasoning-loop, unlike browser-based scrapers that need a container and a browser to boot.

### What it does

- **HTTP-only fetching** — 30s timeout, browser-like User-Agent, follows redirects. No browser overhead.
- **Smart content extraction** — readability first, then `<article>`/`<main>`, then `<body>`; scripts, styles, nav, footers, asides and forms are stripped.
- **Metadata** — page title, meta/OG description, author, `article:published_time` when present.
- **Per-page truncation** — Markdown capped at `maxChars` (default 20,000) so agent context stays bounded.
- **Batch** — one URL per line; one bad URL never kills the batch, failures are reported per row.
- **Safe by default** — only public `http(s)` URLs are fetched; hosts resolving to private, loopback or link-local IPs are refused (SSRF guard).

### Input

| Field | Description |
|---|---|
| `urls` | URLs to convert, one per line (required) |
| `maxChars` | Max Markdown characters per page (default 20,000) |
| `includeImages` | Keep `![alt](url)` image references (default on) |

Example input:

```json
{
  "urls": "https://example.com\nhttps://en.wikipedia.org/wiki/Web_scraping",
  "maxChars": 20000,
  "includeImages": true
}
```

### Output

One dataset row per URL:

| Field | Description |
|---|---|
| `url` / `finalUrl` | Requested URL / URL after redirects |
| `statusCode` | HTTP status of the fetch |
| `title`, `description`, `author`, `publishedAt` | Page metadata |
| `markdown` | Clean Markdown of the main content |
| `charCount` | Length of the Markdown in characters |
| `ok` / `reason` | Success flag; failure reason when `ok` is false |

### Pricing

| Event | Price |
|---|---|
| Page converted | **$0.003** per page successfully converted to Markdown |

You are only charged for pages that convert successfully — failed fetches cost nothing. (Apify platform usage costs are paid by you as usual.)

# Actor input Schema

## `includeImages` (type: `boolean`):

Keep image references as ![alt](url) in the Markdown output.

## `maxChars` (type: `integer`):

Markdown output is truncated to this many characters per page.

## `urls` (type: `string`):

One URL per line. Each page is fetched over HTTP and converted to clean Markdown.

## Actor input object example

```json
{
  "includeImages": true,
  "maxChars": 20000,
  "urls": "https://example.com"
}
```

# Actor output Schema

## `dataset` (type: `string`):

Dataset with one row per converted page: URL, title, metadata and full Markdown.

# 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://example.com"
};

// Run the Actor and wait for it to finish
const run = await client.actor("abdou_009/apify-web-to-markdown").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://example.com" }

# Run the Actor and wait for it to finish
run = client.actor("abdou_009/apify-web-to-markdown").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://example.com"
}' |
apify call abdou_009/apify-web-to-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,abdou_009/apify-web-to-markdown"
        }
    }
}
```

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/IRAJEB9NOAik6toOe/builds/yIrFRf8YftpXIfu1f/openapi.json