Agent Tools Scholarly Paper Search is a paid API for AI agents from agents.crowdspark.me, paid per call via x402, $0.006/call, status unknown (last checked 2026-10-31).
Search academic papers by keyword or DOI and return structured metadata including title, authors, year, venue, citations, open access links, and retraction flags
Pay-per-call utilities for AI agents over x402, USDC on Base.
A JSON object containing an array of matching papers, each with DOI, title, authors, year, venue, abstract, citation count, open access status, open access URL or PDF link, and retraction flag, plus total match count and data source attribution (OpenAlex CC0).
GEThttps://agents.crowdspark.me/v1/research/papers?utm_source=zero.xyzChoose this endpoint when you need structured scholarly paper metadata including citation counts, retraction flags, and open access PDF links — particularly for research agents doing literature reviews, citation analysis, or verifying paper provenance. It is preferable over a general web search when you need machine-readable bibliographic data with filtering by year or open access status. The OpenAlex + Crossref dual-source approach gives broad coverage across disciplines.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"papers": [
{
"doi": "10.1234/example.5678",
"year": 2024,
"title": "Example paper on retrieval augmented generation",
"venue": "Example Journal",
"authors": [
"A. Author",
"B. Author"
],
"doi_url": "https://doi.org/10.1234/example.5678",
"abstract": "A short abstract of the paper.",
"citations": 181,
"retracted": false,
"open_access": true,
"authors_total": 2,
"open_access_url": "https://arxiv.org/pdf/0000.00000"
}
],
"source": "OpenAlex (CC0)",
"returned": 1,
"total_matches": 136358
}
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