# HTML to Markdown & Reader Mode Extractor (`jungle_synthesizer/html-to-markdown-reader`) Actor
Convert any URL or raw HTML to clean markdown, plaintext, and reader-mode metadata. Choose Readability (articles), Turndown (verbatim), or Trafilatura (noisy pages). Outputs title, byline, published date, language, word count, and reading time. FREE — the one-call URL-to-markdown primitive.
- **URL**: https://apify.com/jungle\_synthesizer/html-to-markdown-reader.md
- **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community)
- **Categories:** AI, Developer tools, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per usage
This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use 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
## HTML to Markdown & Reader Mode Extractor
Convert any URL or raw HTML to clean markdown, plaintext, and reader-mode metadata. A FREE, one-call primitive for LLM pipelines, text-processing workflows, and content extraction.
### What it does
Pass a URL or raw HTML, get back:
- **Markdown** — clean, ready for LLM ingestion
- **Plaintext** — stripped of all markup
- **Reader-mode metadata** — title, byline, published date, language, word count, reading time
- **Images** — `[{src, alt}]` list
- **Links** — `[{href, text}]` list
All in a single run. No crawler config needed.
### Extraction modes
| Mode | Best for | How it works |
|------|----------|-------------|
| `readability` (default) | News articles, blog posts, documentation | Mozilla Readability strips navigation, ads, and boilerplate; then Turndown converts the clean article HTML to markdown |
| `turndown` | Preserving the full page structure | Direct Turndown conversion of the full HTML without article extraction — no stripping |
| `trafilatura` | Noisy pages, forums, user-generated content | Cheerio removes script/style/nav/header/footer elements, targets the main content area, then converts to markdown |
### Input
| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `inputs` | array | — | **Required.** Array of `{url?: string, html?: string}` objects |
| `mode` | string | `readability` | Extraction mode: `readability` / `turndown` / `trafilatura` |
| `output` | string | `markdown` | Output format: `markdown` / `plaintext` / `both` |
| `includeImages` | boolean | `true` | Include `images` list in output |
| `preserveLinks` | boolean | `true` | Include `links` list and preserve hyperlinks in markdown |
| `renderJs` | boolean | `false` | Fetch JS-rendered pages via browser (requires more memory) |
| `maxItems` | integer | `15` | Max inputs to process |
#### Example input
```json
{
"inputs": [
{ "url": "https://en.wikipedia.org/wiki/Markdown" },
{ "html": "Hello
World
" }
],
"mode": "readability",
"output": "markdown"
}
````
### Output
One dataset record per input:
| Field | Type | Description |
|-------|------|-------------|
| `input` | string (JSON) | Original input `{url?, html?}` |
| `title` | string | Extracted page title |
| `byline` | string | Author / byline |
| `publishedAt` | string | Published timestamp (ISO 8601, when detectable) |
| `language` | string | Detected language code (ISO 639-1) |
| `markdown` | string | Markdown output |
| `plaintext` | string | Plain-text output |
| `wordCount` | number | Word count |
| `readingTimeMin` | number | Estimated reading time (at 240 wpm) |
| `images` | string (JSON) | `[{src, alt}]` image references |
| `links` | string (JSON) | `[{href, text}]` hyperlinks |
| `mode` | string | `readability` / `turndown` / `trafilatura` |
| `finalUrl` | string | URL after redirects (URL inputs only) |
| `status` | string | `success` / `timeout` / `error` |
| `errorMsg` | string | Error message on failure |
#### Example output record
```json
{
"input": "{\"url\":\"https://en.wikipedia.org/wiki/Markdown\"}",
"title": "Markdown",
"byline": "Contributors to Wikimedia projects",
"publishedAt": "2005-08-09T19:56:00Z",
"language": "en",
"markdown": "# Markdown\n\nMarkdown is a lightweight markup language...",
"wordCount": 2459,
"readingTimeMin": 11,
"images": "[{\"src\":\"/static/images/icons/enwiki-25.svg\",\"alt\":\"Wikipedia\"}]",
"links": "[{\"href\":\"/wiki/Main_Page\",\"text\":\"Main page\"}]",
"mode": "readability",
"finalUrl": "https://en.wikipedia.org/wiki/Markdown",
"status": "success",
"errorMsg": null
}
```
### Pricing
FREE. Compute-billed only — you pay for the Apify platform run time, not per-record. Ideal as a preprocessing step before paid downstream actors (e.g., translation, summarization).
### Use cases
- **LLM context preparation** — fetch and clean web pages before passing to GPT/Claude/Gemini
- **RAG pipeline ingestion** — extract clean text from arbitrary URLs at scale
- **Content archiving** — convert live pages to portable markdown
- **Article extraction** — strip ads and navigation from news/blog content
- **Text analytics** — feed clean plaintext into NLP models
### Technical notes
- HTTP fetch via got-scraping (Chrome TLS fingerprint, follows redirects)
- Concurrency: up to 20 inputs processed in parallel per worker
- Memory: 512 MB default; increase to 1024 MB if `renderJs: true`
- Timeout: 30 seconds per URL fetch
***
**Further reading:** [Technical Data Utilities: DNS Audits, SSL Checks, Satellite Elements, and Bulk Parsing](https://orbtop.com/articles/technical-data-utilities-dns-ssl-satellites/)
# Actor input Schema
## `sp_intended_usage` (type: `string`):
Please describe how you plan to use the data extracted by this crawler.
## `sp_improvement_suggestions` (type: `string`):
Provide any feedback or suggestions for improvements.
## `sp_contact` (type: `string`):
Provide your email address so we can get in touch with you.
## `inputs` (type: `array`):
Array of objects: {url?: string, html?: string}. Either url or html must be provided per entry.
## `output` (type: `string`):
No description
## `mode` (type: `string`):
No description
## `includeImages` (type: `boolean`):
Preserve image references in markdown and emit images list.
## `preserveLinks` (type: `boolean`):
Preserve hyperlinks in markdown and emit links list.
## `renderJs` (type: `boolean`):
When url is provided, use a headless browser to fetch JS-rendered content. Requires more memory (1024 MB+).
## `maxItems` (type: `integer`):
Maximum number of inputs to process. Default is 15.
## Actor input object example
```json
{
"sp_intended_usage": "Describe your intended use...",
"sp_improvement_suggestions": "Share your suggestions here...",
"sp_contact": "Share your email here...",
"inputs": [
{
"url": "https://en.wikipedia.org/wiki/Markdown"
}
],
"output": "markdown",
"mode": "readability",
"includeImages": true,
"preserveLinks": true,
"renderJs": false,
"maxItems": 15
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"sp_intended_usage": "Describe your intended use...",
"sp_improvement_suggestions": "Share your suggestions here...",
"sp_contact": "Share your email here...",
"inputs": [
{
"url": "https://en.wikipedia.org/wiki/Markdown"
}
],
"output": "markdown",
"mode": "readability",
"maxItems": 15
};
// Run the Actor and wait for it to finish
const run = await client.actor("jungle_synthesizer/html-to-markdown-reader").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"sp_intended_usage": "Describe your intended use...",
"sp_improvement_suggestions": "Share your suggestions here...",
"sp_contact": "Share your email here...",
"inputs": [{ "url": "https://en.wikipedia.org/wiki/Markdown" }],
"output": "markdown",
"mode": "readability",
"maxItems": 15,
}
# Run the Actor and wait for it to finish
run = client.actor("jungle_synthesizer/html-to-markdown-reader").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 '{
"sp_intended_usage": "Describe your intended use...",
"sp_improvement_suggestions": "Share your suggestions here...",
"sp_contact": "Share your email here...",
"inputs": [
{
"url": "https://en.wikipedia.org/wiki/Markdown"
}
],
"output": "markdown",
"mode": "readability",
"maxItems": 15
}' |
apify call jungle_synthesizer/html-to-markdown-reader --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=jungle_synthesizer/html-to-markdown-reader",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "HTML to Markdown & Reader Mode Extractor",
"description": "Convert any URL or raw HTML to clean markdown, plaintext, and reader-mode metadata. Choose Readability (articles), Turndown (verbatim), or Trafilatura (noisy pages). Outputs title, byline, published date, language, word count, and reading time. FREE — the one-call URL-to-markdown primitive.",
"version": "0.1",
"x-build-id": "MxVZbla5G5XEYWhwT"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/jungle_synthesizer~html-to-markdown-reader/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-jungle_synthesizer-html-to-markdown-reader",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/jungle_synthesizer~html-to-markdown-reader/runs": {
"post": {
"operationId": "runs-sync-jungle_synthesizer-html-to-markdown-reader",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/jungle_synthesizer~html-to-markdown-reader/run-sync": {
"post": {
"operationId": "run-sync-jungle_synthesizer-html-to-markdown-reader",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"sp_intended_usage",
"sp_improvement_suggestions",
"inputs"
],
"properties": {
"sp_intended_usage": {
"title": "What is the intended usage of this data?",
"minLength": 1,
"type": "string",
"description": "Please describe how you plan to use the data extracted by this crawler."
},
"sp_improvement_suggestions": {
"title": "How can we improve this crawler for you?",
"minLength": 1,
"type": "string",
"description": "Provide any feedback or suggestions for improvements."
},
"sp_contact": {
"title": "Contact Email",
"minLength": 1,
"type": "string",
"description": "Provide your email address so we can get in touch with you."
},
"inputs": {
"title": "Inputs",
"type": "array",
"description": "Array of objects: {url?: string, html?: string}. Either url or html must be provided per entry."
},
"output": {
"title": "Output Format",
"enum": [
"markdown",
"plaintext",
"both"
],
"type": "string",
"description": "",
"default": "markdown"
},
"mode": {
"title": "Extraction Mode",
"enum": [
"readability",
"turndown",
"trafilatura"
],
"type": "string",
"description": "",
"default": "readability"
},
"includeImages": {
"title": "Include Images",
"type": "boolean",
"description": "Preserve image references in markdown and emit images list.",
"default": true
},
"preserveLinks": {
"title": "Preserve Links",
"type": "boolean",
"description": "Preserve hyperlinks in markdown and emit links list.",
"default": true
},
"renderJs": {
"title": "Render JavaScript",
"type": "boolean",
"description": "When url is provided, use a headless browser to fetch JS-rendered content. Requires more memory (1024 MB+).",
"default": false
},
"maxItems": {
"title": "Max Items",
"type": "integer",
"description": "Maximum number of inputs to process. Default is 15.",
"default": 15
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```