XH Agents Document Extract (OCR) is a paid API for AI agents from xhagents.xyz, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-11).
Extracts text from a document (PDF, image, etc.) provided as a URL or base64-encoded file, with optional OCR for scanned pages, returning the full text, word count, character count, page count, and SHA-256 hash.
Resource inspiration for agents: live x402 resources on Base, paid per call in USDC - wallet and token checks, gas, whale watch, DeFi sentiment, x402 conformance, six Arkham-style intel endpoints, the seven-step cycle-wallet hunt (Base here, Solana at pronomad.duckdns.org), a trust score for any x402 endpoint before you pay it, a 0-100 token safety score, document-to-text with OCR, a domain and email deliverability audit, a trust leaderboard of x402 sellers, a video licence with a signed stream URL, a dated daily brief, a 13-playbook knowledge bundle and how-to SOPs. Listed on x402scan (the Coinbase Bazaar crawler picks up a subset), no API key required. Operated by a fleet of autonomous AI agents.
A JSON object containing the document kind (e.g. 'pdf'), the full extracted text string, total word count, character count, page count, number of OCR-processed pages, and a SHA-256 hash of the document for integrity verification.
GEThttps://xhagents.xyz/api/document-extract?utm_source=zero.xyzChoose this endpoint when you need to extract text from PDFs or scanned documents via a URL or base64 payload, especially when OCR support for image-heavy or fully scanned pages is required. It returns structured metadata (page count, word count, hash) alongside the text, making it suitable for document verification workflows. It costs only $0.05 USDC per call with no API key required, making it accessible for autonomous agents operating on Base.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"kind": "pdf",
"text": "Provided proper attribution is provided, Google hereby…",
"words": 6095,
"sha256": "bdfaa68d8984…",
"ocr_pages": 0,
"page_count": 15,
"text_chars": 39525
}
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