# Clean Web HTML to LLM-Ready Markdown Converter (`n4d.h1dr/html-to-llm-markdown`) Actor

Deterministic, zero-latency converter that strips boilerplate, ads, and scripts from HTML into clean, token-efficient Markdown for LLM & RAG pipelines.

- **URL**: https://apify.com/n4d.h1dr/html-to-llm-markdown.md
- **Developed by:** [Nadim Hider](https://apify.com/n4d.h1dr) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 processed items

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

## Clean Web HTML to LLM-Ready Markdown Converter

An ultra-fast, deterministic Apify Actor that strips away boilerplate, navigational noise, tracking scripts, and styling from messy HTML documents, outputting clean, token-efficient GitHub-flavored Markdown specifically formatted for Large Language Models (LLMs), RAG pipelines, and AI agent workflows.

***

### 🚀 Why Use This Actor?

Feeding raw web pages or messy HTML directly into LLMs wastes up to **70% of your prompt tokens** on boilerplate headers, footers, stylesheets, SVG icons, and ads. This Actor provides a zero-latency, deterministic transformation pipeline that:

- **Reduces LLM Token Usage**: Cuts token counts drastically, saving significant API costs on OpenAI, Anthropic, Gemini, and local LLMs.
- **Zero Hallucination / 100% Deterministic**: Uses strict structural DOM parsing (`BeautifulSoup4` + `markdownify`) rather than probabilistic AI models.
- **Preserves Critical Content**: Retains semantic headings, lists, inline formatting, code snippets, and Markdown tables.
- **Extracts Key Meta Fields**: Pulls document titles, SEO meta descriptions, and heading hierarchies into structured JSON attributes alongside the markdown body.
- **Ideal for AI Automations**: Seamlessly plugs into **n8n**, **Make.com**, **LangChain**, **LlamaIndex**, and **Apify MCP** servers.

***

### 📥 Input Schema

| Field | Type | Default | Description |
|---|---|---|---|
| `documents` | Array of Objects | *Sample Demo Document* | Array of objects with `source_id` and raw `html` strings. |
| `strip_links` | Boolean | `false` | When `true`, strips hyperlinks while preserving anchor text to minimize token overhead. |
| `heading_style` | String | `"ATX"` | `"ATX"` uses `# Heading`, while `"UNDERLINE"` uses `===` and `---`. |
| `extract_tables` | Boolean | `true` | Formats HTML tables into standard Markdown grid tables. |

#### Sample Input JSON

```json
{
  "documents": [
    {
      "source_id": "article-101",
      "html": "<html><head><title>AI Trends</title></head><body><header>Nav</header><main><h1>Top Trends</h1><p>Autonomous agents are scaling rapidly.</p></main><footer>Footer</footer></body></html>"
    }
  ],
  "strip_links": false,
  "heading_style": "ATX",
  "extract_tables": true
}
```

***

### 📤 Output Dataset Format

Each processed document yields a structured record in the default dataset:

```json
{
  "source_id": "article-101",
  "title": "AI Trends",
  "meta_description": "",
  "markdown": "# Top Trends\n\nAutonomous agents are scaling rapidly.",
  "character_count": 52,
  "estimated_tokens": 13,
  "headings": [
    "H1: Top Trends"
  ],
  "status": "success"
}
```

***

### 💰 Pay-Per-Event (PPE) Pricing

This Actor utilizes Apify's modern **Pay-Per-Event** billing model:

- **Event Name**: `item-processed`
- **Cost**: Only **$0.001 per document** ($1.00 per 1,000 documents).
- **No Monthly Minimums**: Pay only for the documents you actually convert. Compute overhead is practically zero, providing the highest ROI for production ingestion pipelines.

***

### 🔌 API & Python Client Example

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "documents": [
        {"source_id": "doc1", "html": "<h1>Hello World</h1><p>Content to clean.</p>"}
    ]
}

run = client.actor("YOUR_USERNAME/html-to-llm-markdown").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["markdown"])
```

# Actor input Schema

## `documents` (type: `array`):

List of HTML documents or raw page snippets to convert into clean, token-efficient Markdown.

## `strip_links` (type: `boolean`):

If enabled, removes URL hyperlinks while retaining the anchor text, saving additional LLM tokens.

## `heading_style` (type: `string`):

ATX uses '#' for headings; UNDERLINE uses '===' and '---'.

## `extract_tables` (type: `boolean`):

Formats HTML tables into standard GitHub-flavored Markdown tables.

## Actor input object example

```json
{
  "documents": [
    {
      "source_id": "welcome-demo",
      "html": "<html><head><title>Welcome to LLM Markdown Converter</title><meta name=\"description\" content=\"Fast, deterministic text formatting for AI\"></head><body><header><nav><a href=\"#\">Home</a></nav></header><main><h1>AI Data Cleaning Made Easy</h1><p>This utility strips away bloated HTML tags, scripts, and navigation bars, leaving only pure, structured Markdown optimized for LLM context windows.</p><table><tr><th>Feature</th><th>Benefit</th></tr><tr><td>Boilerplate Removal</td><td>Saves up to 70% token costs</td></tr><tr><td>Deterministic</td><td>Zero hallucinations, 100% reliable</td></tr></table></main><footer>Copyright 2026</footer></body></html>"
    }
  ],
  "strip_links": false,
  "heading_style": "ATX",
  "extract_tables": true
}
```

# 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 = {
    "documents": [
        {
            "source_id": "welcome-demo",
            "html": "<html><head><title>Welcome to LLM Markdown Converter</title><meta name=\"description\" content=\"Fast, deterministic text formatting for AI\"></head><body><header><nav><a href=\"#\">Home</a></nav></header><main><h1>AI Data Cleaning Made Easy</h1><p>This utility strips away bloated HTML tags, scripts, and navigation bars, leaving only pure, structured Markdown optimized for LLM context windows.</p><table><tr><th>Feature</th><th>Benefit</th></tr><tr><td>Boilerplate Removal</td><td>Saves up to 70% token costs</td></tr><tr><td>Deterministic</td><td>Zero hallucinations, 100% reliable</td></tr></table></main><footer>Copyright 2026</footer></body></html>"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("n4d.h1dr/html-to-llm-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 = { "documents": [{
            "source_id": "welcome-demo",
            "html": "<html><head><title>Welcome to LLM Markdown Converter</title><meta name=\"description\" content=\"Fast, deterministic text formatting for AI\"></head><body><header><nav><a href=\"#\">Home</a></nav></header><main><h1>AI Data Cleaning Made Easy</h1><p>This utility strips away bloated HTML tags, scripts, and navigation bars, leaving only pure, structured Markdown optimized for LLM context windows.</p><table><tr><th>Feature</th><th>Benefit</th></tr><tr><td>Boilerplate Removal</td><td>Saves up to 70% token costs</td></tr><tr><td>Deterministic</td><td>Zero hallucinations, 100% reliable</td></tr></table></main><footer>Copyright 2026</footer></body></html>",
        }] }

# Run the Actor and wait for it to finish
run = client.actor("n4d.h1dr/html-to-llm-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 '{
  "documents": [
    {
      "source_id": "welcome-demo",
      "html": "<html><head><title>Welcome to LLM Markdown Converter</title><meta name=\\"description\\" content=\\"Fast, deterministic text formatting for AI\\"></head><body><header><nav><a href=\\"#\\">Home</a></nav></header><main><h1>AI Data Cleaning Made Easy</h1><p>This utility strips away bloated HTML tags, scripts, and navigation bars, leaving only pure, structured Markdown optimized for LLM context windows.</p><table><tr><th>Feature</th><th>Benefit</th></tr><tr><td>Boilerplate Removal</td><td>Saves up to 70% token costs</td></tr><tr><td>Deterministic</td><td>Zero hallucinations, 100% reliable</td></tr></table></main><footer>Copyright 2026</footer></body></html>"
    }
  ]
}' |
apify call n4d.h1dr/html-to-llm-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,n4d.h1dr/html-to-llm-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/PwrYDHQJZpSwacJQt/builds/wBbE7qIeusuF9emWb/openapi.json