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Agent Read Proxy
x402
Agent Read Proxy is a paid API for AI agents from agent-read-proxy.agent-read-proxy.workers.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-31).
Fetches a public web page or document (PDF, Word, Excel, CSV) and returns clean readable content as plain text or Markdown with metadata such as title, author, publish date, and language.
Price / call$0.002
Success—
StatusUnknown
How this service works
Fetch a public web page and return its readable content as JSON: plain text or Markdown (headings, lists, links kept), plus title, description, author, publish date, site name, language and preview image. Ads, menus and scripts are stripped. Also reads PDF, Word, Excel and CSV links. Failed fetches are not charged.
Output
A JSON object containing the clean readable content of the requested page or document in plain text or Markdown format, along with metadata: title, language, canonical URL, author, publish date, site name, preview image URL, word count, fetch timestamp, and a truncated flag indicating whether the content was cut short.
Example use cases
Research assistant reading news articles
“Read the article at https://www.bbc.com/news/technology-67890 and give me a clean markdown version of the full text, stripping out any ads or menus.”
AI agent parsing a linked PDF report
“There's a PDF at https://example.gov/annual-report-2024.pdf — can you extract the readable text from it and tell me when it was published?”
Competitive intelligence from a competitor's blog
“Fetch the blog post at https://competitor.com/blog/our-new-product and return the plain text content along with the title, author, and publish date.”
Technical details
Endpoint
GEThttps://agent-read-proxy.agent-read-proxy.workers.dev/v1/read?utm_source=zero.xyzWhen to prefer
Choose this endpoint when an AI agent needs to read the human-readable content of any public URL — whether a web article, blog post, Wikipedia page, PDF, Word doc, Excel file, or CSV — and get back clean text or Markdown stripped of ads, navigation, and scripts. It is especially valuable when you also need structured metadata (title, author, publish date, language) alongside the content. Prefer this over raw HTTP fetches when you want content already cleaned and parsed, and over general web search APIs when you have a specific URL to read rather than a query to resolve.
Side effects
- URL is unreachable or returns a non-200 HTTP status — fetch fails, not charged
- URL points to a private or paywalled page — content may be empty or partial
- Unsupported document type (e.g. ZIP, binary) — returns error
- URL is malformed or missing — validation error on required parameter
- Content extraction yields very little text (e.g. heavily JavaScript-rendered page) — partial or empty content returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"url": "https://en.wikipedia.org/wiki/Motocross",
"title": "Motocross - Wikipedia",
"format": "markdown",
"language": "en",
"markdown": "From Wikipedia, the free encyclopedia\n\nOff-road motorcycle racing held on enclosed off-road circuits\n\n## History\n\n...",
"truncated": false,
"fetched_at": "2026-10-28T01:30:00.000Z",
"word_count": 4463,
"canonical_url": "https://en.wikipedia.org/wiki/Motocross"
}
}Tags
x402
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