Web Page → Markdown Converter

Convert any URL to clean Markdown plus structured metadata (title, author, date, lang, image, tags). Uses trafilatura — the same library Common Crawl uses. LLM-ready output. Batch up to 500 URLs. $0.005 per URL.

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⚡ Run in 30 seconds

Click Start with default settings — fetches the example URL and returns clean Markdown text plus title, author, publication date, language, and image metadata, all ready to pipe into an LLM. No API key needed.

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Input Parameters

Parameter	Type	Default	Description
urls	array	[]	List of URLs to convert. Each is billed separately.
url	string	``	Single URL (used when 'urls' is empty).
includeComments	boolean	false	Include reader comments / discussion sections.
includeTables	boolean	true	Render HTML tables as Markdown tables.
deduplicate	boolean	true	Drop repeated boilerplate (nav, footer, ads).
userAgent	string	``	Custom UA string. Default looks like a desktop browser.

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Why this exists

Most LLM pipelines need clean article-body text — but raw HTML is 60-90% boilerplate (nav, footer, ads, JS, related stories). Existing solutions:

• Browserless / Puppeteer: complex setup, $30+/mo
• Mercury Parser: deprecated
• Diffbot: $299/mo minimum
• Readability.js: requires running Node

This actor wraps trafilatura — the gold-standard Python library used by Common Crawl and most LLM training pipelines — into a one-call API. Pass a URL list, get clean Markdown + metadata back.

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What you get per row

Field	Example	Notes
url	https://...	input URL
ok	true	did extraction succeed
title	Bitcoin — Wikipedia	from <title> or og
author	Wikipedia contributors
description	Bitcoin is a cryptocurrency...
date_published	2025-12-01
language	en	auto-detected
sitename	Wikipedia
tags	["cryptocurrency", "blockchain"]
categories	["Technology"]
image	https://...	hero image
markdown	# Bitcoin\n\nBitcoin is...	clean body
char_count	48230
word_count	7842

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Quick start

Single URL

{
  "url": "https://en.wikipedia.org/wiki/Bitcoin"
}

Batch of URLs

{
  "urls": [
    "https://techcrunch.com/article-1",
    "https://www.theverge.com/article-2",
    "https://www.wired.com/article-3"
  ],
  "includeTables": true,
  "deduplicate": true
}

Custom User-Agent (some sites require it)

{
  "url": "https://...",
  "userAgent": "Mozilla/5.0 (compatible; YourBot/1.0; +https://yourdomain.com/bot)"
}

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Pricing

Pay-Per-Event: $0.005 per URL processed.

Run	URLs	Cost
Single article	1	$0.005
Batch of 100	100	$0.50
Daily crawl of 1K URLs	1000	$5.00

Vs Diffbot ($299/mo), Mercury ($199/mo for similar tier), this is 40-60x cheaper for typical volumes.

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Common pipeline patterns

Feed to Claude / GPT for summarization

# 1. Extract clean text
curl -X POST "https://api.apify.com/v2/acts/gochujang~web-to-markdown/runs?token=$T" \
  -d '{"url":"..."}'

# 2. Pipe markdown to Claude
curl -X POST https://api.anthropic.com/v1/messages \
  -d "{\"messages\":[{\"role\":\"user\",\"content\":\"Summarize: $MARKDOWN\"}]}"

RSS-style aggregator

1. Sitemap URL Discovery to get all article URLs
2. Filter by lastmod (recent only)
3. This actor to convert each to Markdown
4. Store in your DB / Notion / Obsidian

Personal read-it-later

Schedule this actor with your "saved articles" Google Sheet → get clean markdown into Obsidian / Logseq daily.

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Use cases

1. LLM input prep — Clean text for RAG / fine-tuning / summarization
2. Content curation — Newsletter / digest aggregation
3. SEO research — Compare clean content across competitors
4. Archiving — Read-it-later in Markdown format
5. Translation pipelines — Strip boilerplate before sending to MT

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Data source / engine

• Engine: trafilatura — actively maintained, used by Common Crawl
• Fallback: Returns ok: false with error message if a page can't be extracted (paywall, JS-heavy SPA without SSR, etc.)

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Limitations

• JS-only sites: Pages that render entirely in client-side JS may return empty markdown. For those, use a browser-rendering actor (Playwright/Puppeteer-based).
• Paywalls: This actor doesn't bypass paywalls.
• Comments / discussion sections: Off by default; enable with includeComments: true.

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Related actors (same author)

• HTML Metadata Extractor — Just metadata (OG, Twitter, JSON-LD) without article body
• Sitemap URL Discovery — Find all URLs to feed into this actor
• PDF Text Extractor — PDF version
• JSON Schema Generator

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Feedback

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