URL to Clean Markdown — for AI Agents avatar

URL to Clean Markdown — for AI Agents

Pricing

from $2.00 / 1,000 pages

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URL to Clean Markdown — for AI Agents

URL to Clean Markdown — for AI Agents

Convert any web page into clean, LLM-ready Markdown. Charged only on successful conversion. MCP & x402 ready.

Pricing

from $2.00 / 1,000 pages

Rating

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Developer

Öge

Öge

Maintained by Community

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0

Bookmarked

2

Total users

1

Monthly active users

2 days ago

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Give it a web page URL, get back clean, LLM-ready Markdown — main content only, no nav/ads/boilerplate. Built for AI agents, RAG pipelines and research tools.

When to use this tool

Call this whenever an agent needs to read a web page as text: feeding a page into an LLM, building a RAG corpus, summarizing an article, or extracting documentation. It strips the page down to its real content (via Mozilla Readability) and returns Markdown.

Input

{ "urls": [{ "url": "https://en.wikipedia.org/wiki/Model_Context_Protocol" }], "maxItems": 100 }
  • urls — one or more page URLs (also accepts plain strings)
  • maxItems — cap on pages per run (default 100)
  • proxy — route through Apify Proxy to reduce blocks (default: on)

Output — one dataset item per page

{
"url": "https://en.wikipedia.org/wiki/Model_Context_Protocol",
"title": "Model Context Protocol",
"byline": null,
"excerpt": "An open standard for connecting AI assistants to tools and data...",
"lang": "en",
"wordCount": 1240,
"markdown": "# Model Context Protocol\n\n...",
"scrapedAt": "2026-07-14T12:00:00.000Z"
}

Pricing — charge on success

Pay per result. You are charged only for pages successfully converted to Markdown. If a page is blocked or has no readable content, nothing is pushed and nothing is charged.

Notes

  • Content extraction via Mozilla Readability + Turndown (same engine family as Firefox Reader View).
  • Apify Proxy included to reduce blocking.
  • MCP & x402 compatible — callable directly by AI agents, no API key required via x402.
  • Returns clean Markdown ready to drop straight into an LLM context window.