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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
| When | Result | HTTP | Time | Price |
|---|---|---|---|---|
| 3 h ago | Passed | 402 | 46 ms | $0.009 |
| 8 h ago | Passed | 402 | 48 ms | $0.009 |