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Papers Search

by FiatDock in Search & web

x402 APIPassing, checked 3 h ago

Find academic papers in any field - title, authors, year, venue, DOI, citation count, open-access link and abstract - from OpenAlex (~250M works incl. arXiv and PubMed; Crossref answers if OpenAlex is down). Filter by year range and open access; sort by relevance, citations or date. Send {} to search the published example query. A search with no result is not charged. Pay-per-call via x402.

POST https://fiatdock.com/v1/papers/search

Last 30 days

All checks passedSome failedAll failedNot checked
Uptime
100%
Response time
46 ms typical, 46 ms slowest 5%
Last check
3 h ago
Next check
any minute now

How to call it

# See the payment challenge (nothing is charged)
curl -i -X POST "https://fiatdock.com/v1/papers/search" \
  -H "content-type: application/json" \
  -d '{"limit":5,"query":"large language model agents"}'
import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { ExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

const client = new x402Client().register(
  "eip155:8453",
  new ExactEvmScheme(privateKeyToAccount(process.env.AGENT_KEY)),
);
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? Preflight it first for $0.005:
// GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Ffiatdock.com%2Fv1%2Fpapers%2Fsearch
const res = await pay("https://fiatdock.com/v1/papers/search", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({"limit":5,"query":"large language model agents"}),
});
console.log(await res.json());

Example input

{
  "limit": 5,
  "query": "large language model agents"
}

Example output

{
  "asOf": "2026-10-05T00:00:00.000Z",
  "count": 1,
  "filters": {
    "fromYear": null,
    "openAccessOnly": false,
    "sort": "relevance",
    "toYear": null
  },
  "note": "Titles, author names and abstracts are the authors' and publishers' text.",
  "papers": [
    {
      "abstract": "Autonomous agents have long been a research focus in academic and industry communities…",
      "authorCount": 11,
      "authors": [
        "Lei Wang",
        "Chen Ma",
        "Xueyang Feng"
      ],
      "citedBy": 1688,
      "doi": "10.1007/s11704-024-40231-1",
      "openAccess": true,
      "openAccessUrl": "https://link.springer.com/article/10.1007/s11704-024-40231-1",
      "publicationDate": "2024-03-22",
      "title": "A survey on large language model based autonomous agents",
      "type": "article",
      "url": "https://doi.org/10.1007/s11704-024-40231-1",
      "venue": "Frontiers of Computer Science",
      "year": 2024
    }
  ],
  "query": "large language model agents",
  "source": "OpenAlex (api.openalex.org, CC0 metadata)",
  "totalMatched": 1158374
}

Security scan

  • No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

Recent checks

WhenResultHTTPTimePrice
3 h agoPassed40246 ms$0.009
8 h agoPassed40248 ms$0.009