Pricing

from $3.00 / 1,000 url converteds

HTML to Markdown Converter - Bulk Web Content to MD

Extract main article content from any website and convert to clean Markdown including headings, links, images, tables, and code blocks. Perfect for LLM training, AI pipelines, and documentation. Export data, run via API, schedule and monitor runs, or integrate with other tools.

Pricing

from $3.00 / 1,000 url converteds

Rating

0.0

(0)

Developer

Alessandro Santamaria

Actor stats

Bookmarked

Total users

Monthly active users

2 days ago

Last modified

Features

Readability-style extraction — returns the article body, not the whole page
Tables preserved — HTML tables become proper Markdown tables with pipes and separators
Code blocks preserved — <pre> and <code> blocks kept intact, fenced and ready for LLMs
Images preserved — alt text, titles, and absolute URLs
Nested structures — lists inside lists, blockquotes, headings all handled correctly
Strikethrough — <s>, <strike>, <del> converted to ~~text~~
Outbound link discovery — every external link the page points to, with anchor text
Smart metadata — page title, meta description, Open Graph, content type classification
Parallel processing — 6 URLs at a time for fast bulk conversion
Tiny footprint — minimal compute usage keeps your bill low

Example Output

Input URL: https://en.wikipedia.org/wiki/Markdown

# Markdown

**Markdown** is a lightweight [markup language](/wiki/Markup_language) for
creating [formatted text](/wiki/Formatting_(word_processing)) using a
[plain-text editor](/wiki/Text_editor). [John Gruber](/wiki/John_Gruber)
created Markdown in 2004 as an easy-to-read markup language.

## Examples

Text using Markdown syntax:

```
# Heading

Paragraphs are separated
by a blank line.

**bold**, *italic*, `monospace`
```

Bullet lists nested within numbered list:

1. fruits
   - apple
   - banana
2. vegetables
   - carrot
   - broccoli

## See also

- [CommonMark](/wiki/CommonMark)
- [reStructuredText](/wiki/ReStructuredText)
- [AsciiDoc](/wiki/AsciiDoc)

Clean, readable, LLM-ready. No navigation menus, no "Toggle sidebar", no language switcher.

Input

{
  "urls": [
    "https://en.wikipedia.org/wiki/Markdown",
    "https://blog.apify.com/"
  ],
  "extractMainContent": true,
  "includeImages": true,
  "includeTables": true,
  "includeStrikethrough": true,
  "followRedirects": true,
  "maxContentLengthKB": 500,
  "timeoutSeconds": 30
}

Field	Type	Default	Description
`urls`	array of strings	required	URLs to fetch and convert
`extractMainContent`	boolean	`true`	Strip navigation, ads, footers — return only article body
`includeImages`	boolean	`true`	Keep image links in output
`includeTables`	boolean	`true`	Enable table conversion plugin
`includeStrikethrough`	boolean	`true`	Enable `~~strikethrough~~` plugin
`followRedirects`	boolean	`true`	Follow HTTP 3xx redirects
`maxContentLengthKB`	integer	`500`	Per-URL HTML size cap
`timeoutSeconds`	integer	`30`	Per-URL download + parse timeout

Output

One record per input URL:

{
  "url": "https://en.wikipedia.org/wiki/Markdown",
  "final_url": "https://en.wikipedia.org/wiki/Markdown",
  "success": true,
  "error": "",
  "page_title": "Markdown - Wikipedia",
  "page_description": "Markdown is a lightweight markup language...",
  "markdown": "# Markdown\n\n**Markdown** is a lightweight...",
  "markdown_length": 36278,
  "word_count": 2907,
  "html_length": 195413,
  "content_type": "article",
  "images": [
    "https://upload.wikimedia.org/wikipedia/commons/..."
  ],
  "links": [
    { "text": "John Gruber", "url": "https://daringfireball.net/" }
  ],
  "main_content_only": true,
  "scraped_at": "2026-04-07T12:34:56Z"
}

content_type is one of: article, blog, documentation, generic — detected from JSON-LD schema, <article> tags, and code block density.

Main Content Extraction

When extractMainContent is enabled, the actor tries these strategies in order:

JSON-LD articleBody — Schema.org Article, BlogPosting, or NewsArticle
CSS selectors — .mw-parser-output, .article-content, .post-content, .entry-content, .article-body, .post-body, #mw-content-text, #content, #main
Semantic tags — <article>, <main>, [role=main]
Body fallback — <body> with navigation, footer, aside, script, style, forms, and common noise classes removed

This gives much cleaner Markdown output for articles and blog posts than a naive conversion of the entire page.

Use Cases

LLM training data — build high-quality datasets from web content for fine-tuning
AI RAG pipelines — ingest web content into vector DBs (Pinecone, Weaviate, Qdrant) as clean chunks
Content archiving — save articles, blog posts, and documentation as portable Markdown files
Documentation conversion — migrate legacy HTML docs to Markdown-based static site generators
Newsletter generation — extract clean article text for email newsletters without HTML clutter
Note-taking workflows — save web articles directly to Obsidian, Notion, Logseq, or any Markdown tool
Research and summarization — feed AI summarizers with the actual content, not navigation menus
Knowledge base construction — build searchable knowledge bases from public web content
Competitor content analysis — bulk-convert competitor blogs for analysis

Pricing

Pay-per-event — you only pay for URLs you actually convert:

Event	Price
Actor start	$0.001
URL converted	$0.003

1,000 URLs ≈ $3.00

No hidden platform fees, no surprise compute charges.

RSS Feed Reader — pull article URLs from RSS feeds, then pipe into this actor
PDF Text Extractor — convert PDFs to plain text instead of HTML
Website Content Crawler — crawl entire sites, not just a URL list
Website Tech Stack Detector — identify the CMS and tech behind any site

Built by santamaria-automations.

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