# Web to Markdown — LLM Web Page Reader (`drain54/web-to-markdown`) Actor

Extract clean, LLM-ready Markdown, titles, and metadata from any public webpage. Strips ads, navigation, and boilerplate.

- **URL**: https://apify.com/drain54/web-to-markdown.md
- **Developed by:** [Indra Darmawan](https://apify.com/drain54) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.005 / extracted web markdown

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

## Web to Markdown — LLM Web Page Reader

Extract clean, LLM-ready Markdown and structured metadata from any webpage in milliseconds. Strip ads, popups, cookie notices, and navigation boilerplate so your AI agents, RAG pipelines, or fine-tuning datasets get pure content.

***

### What does Web to Markdown Reader do?

Web to Markdown takes any public webpage URL and returns:

- **Clean Markdown content**: Headings, lists, code blocks, tables, and clean text.
- **Page Metadata**: Title, meta description, and canonical URL.
- **Token Estimation**: Pre-computed character and token counts (~len/4) for LLM context planning.
- **Fast Execution**: Uses lightweight extraction without heavy headless browser overhead.

### Why use Web to Markdown Reader?

- **Zero Bloat for LLMs**: Raw HTML easily wastes 80-90% of token budgets on CSS, JS, and HTML boilerplate. This Actor filters straight to the article or main content.
- **Pay Per Event (PPE)**: Pay only for what you extract, avoiding expensive monthly subscriptions.
- **Agent & MCP Friendly**: Easily integrated via Apify API, Apify MCP, or webhook automation.

***

### How to use

1. Enter the **Page URL** you want to extract.
2. Toggle whether to include markdown hyperlinks or images.
3. Click **Start** or call via API.
4. Download or consume results directly in JSON, CSV, or Markdown.

#### Input Example

```json
{
  "url": "https://news.ycombinator.com",
  "include_links": true,
  "include_images": false
}
```

#### Output Example

```json
{
  "url": "https://news.ycombinator.com",
  "title": "Hacker News",
  "description": "",
  "content": "# Hacker News\n\n1. Qwen-Image-2.1: Compact, efficient...\n2. Key symbols we lost to time...",
  "length": 4623,
  "estimated_tokens": 1155,
  "elapsed_ms": 320
}
```

***

### Output Fields

| Field | Type | Description |
|---|---|---|
| `url` | string | Target webpage URL |
| `title` | string | Extracted webpage title |
| `description` | string | Meta description tag |
| `content` | string | Clean Markdown formatted text |
| `length` | integer | Character length of content |
| `estimated_tokens` | integer | Estimated LLM tokens (~length / 4) |
| `elapsed_ms` | integer | Execution time in milliseconds |

***

### API Integration

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("drain54/web-to-markdown").call(
    run_input={"url": "https://example.com"}
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["content"])
```

# Actor input Schema

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

The URL of the webpage to extract Markdown from.

## `include_links` (type: `boolean`):

Preserve markdown hyperlinks.

## `include_images` (type: `boolean`):

Preserve markdown image links.

## Actor input object example

```json
{
  "url": "https://news.ycombinator.com",
  "include_links": true,
  "include_images": false
}
```

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

// Run the Actor and wait for it to finish
const run = await client.actor("drain54/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 = { "url": "https://news.ycombinator.com" }

# Run the Actor and wait for it to finish
run = client.actor("drain54/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 '{
  "url": "https://news.ycombinator.com"
}' |
apify call drain54/web-to-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,drain54/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/5Z13wZtsgbRfUvasT/builds/bhSh7HAWl9V5coSff/openapi.json