AgentFeed Scholarly Paper Lookup by DOI is a paid API for AI agents from x402.ochinimus.app, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-23).
Fetches metadata for a scholarly paper by its DOI, returning title, authors, venue, year, citation count, open-access URL, and abstract when available.
Crypto market data for AI agents (liquidations, funding, open interest, prices), Solana pre-trade checks, OFAC sanctions screening, scholarly papers, utilities and fixed-purpose language tasks (OCR, translate, summarize, extract, classify, prompt-injection check, transcribe). Paid per call in USDC over x402 on Solana, Base, Polygon, Arbitrum, Arc, Algorand, Optimism, Monad or Avalanche. High-frequency callers pay half price (minimum $0.0005) through batch-settlement (open a channel once, then off-chain vouchers) on Base, Polygon, Arbitrum or Circle Gateway nanopayments on Base, Polygon, Arbitrum, Arc. No API key or account is needed to pay per call. Bots that cannot pay x402 can buy a prepaid key once ($0.25, $1, $5, $20; page at /keys) and send it as X-AgentFeed-Key: each call then costs half the route price, minimum $0.0005, drawn from the balance (GET /api/keys/balance, free). A 30-day bot pass for /api/liq-feed is $25 flat, with nothing drawn per call (/api/keys/buy-pass).
A JSON object containing the paper's DOI, type, year, title, venue, authors list, total author count, language, citation count, abstract (if available), open-access status and URL, OpenAlex ID, data source attribution, license, and a flag indicating whether the result was served from cache.
GEThttps://x402.ochinimus.app/api/paper/%7Bdoi%7D?utm_source=zero.xyzChoose this endpoint when you need structured bibliographic metadata for a specific paper and have its DOI — it's ideal for citation enrichment, open-access discovery, and literature review automation. It does not require an API key (pay-per-call via x402 in USDC) and sources data from OpenAlex, which has broad coverage of academic literature. Prefer this over general web search when you need machine-readable, structured academic metadata rather than raw HTML.
| Field | Type | Description |
|---|---|---|
| required | string | |
| properties | string |
{
"type": "json",
"example": {
"data": {
"doi": "10.1038/nature14539",
"type": "article",
"year": 2015,
"title": "Deep learning",
"venue": "Nature",
"cached": false,
"source": "OpenAlex (openalex.org)",
"authors": [
"Yann LeCun",
"Yoshua Bengio",
"Geoffrey E. Hinton"
],
"license": "CC0 (OpenAlex data is public domain)",
"abstract": null,
"cited_by": 83602,
"language": "en",
"open_access": {
"url": "https://hal.science/hal-04206682",
"is_oa": true
},
"openalex_id": "https://openalex.org/W2919115771",
"authors_total": 3
},
"paid": true,
"tool": "get_paper"
}
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