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The Stall — Research Paper Search
x402
The Stall — Research Paper Search is a paid API for AI agents from the-stall.intuitek.ai, paid per call via x402, $0.034/call, status unknown (last checked 2026-09-13).
Searches academic literature by keyword or natural language query, returning ranked paper metadata with optional filters for recency, citation count, and open-access availability.
Price / call$0.034
Success—
StatusUnknown
How this service works
Academic paper search across 250M+ works via OpenAlex (free, no key). Returns top papers with title, authors, year, DOI, citation count, open-access status, and primary research topic. Covers all disciplines: AI/ML, medicine, physics, economics, law, biology, and more. Supports relevance, citation-count, and recency sorting; open-access filtering; and year-range constraints. Use for literature review, prior-art search, citation building, or finding the seminal papers in any field.
Output
A list of up to 10 research papers, each including title, authors, publication year, abstract snippet, citation count, DOI, and open-access PDF URL if available, ranked by the chosen sort order (relevance, citation count, or recency).
Example use cases
Example prompt
“Find me the 5 most relevant academic papers on transformer attention mechanisms, preferably open-access ones published after 2020 — sort by relevance.”
Technical details
Endpoint
GEThttps://the-stall.intuitek.ai/cap/research-paper-searchWhen to prefer
Use this endpoint when an agent needs to surface peer-reviewed academic literature by natural language or keyword query, especially with control over sort order (relevance, citations, or recency) and open-access filtering. Prefer over general web search when scholarly provenance and citation metadata matter.
Side effects
- Empty results if the query is too niche or misspelled
- Payment failure if USDC balance on Base is insufficient
- Rate limiting or timeout if the underlying OpenAlex API is slow
- min_year filter too restrictive resulting in zero results
- Query too broad returning low-relevance papers
Input
{
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"sort": "relevant",
"limit": 5,
"query": "artificial intelligence"
}
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| required | string | |
| properties | string |
Output
{
"query": "artificial intelligence",
"papers": [
{
"doi": "https://doi.org/10.5860/choice.33-1577",
"year": 1995,
"title": "Artificial intelligence: a modern approach",
"oa_url": "https://doi.org/10.5281/zenodo.11381885",
"authors": [
"Dr. Anil Kumar",
"Sivasubramanian Balasubramanian",
"Dr. Haewon Byeon",
"Prof. Ganesh Vasudeo Manerkar"
],
"abstract": "The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Sys",
"open_access": true,
"primary_topic": "Cognitive Computing and Networks",
"cited_by_count": 22246
},
{
"doi": "https://doi.org/10.1016/0004-3702(96)00007-0",
"year": 1996,
"title": "Artificial intelligence: A modern approach",
"oa_url": null,
"authors": [
"Nils J. Nilsson"
],
"abstract": null,
"open_access": false,
"primary_topic": "Logic, programming, and type systems",
"cited_by_count": 10701
},
{
"doi": "https://doi.org/10.1038/s41591-018-0300-7",
"year": 2018,
"title": "High-performance medicine: the convergence of human and artificial intelligence",
"oa_url": null,
"authors": [
"Eric J. Topol"
],
"abstract": null,
"open_access": false,
"primary_topic": "Artificial Intelligence in Healthcare and Education",
"cited_by_count": 8463
},
{
"doi": null,
"year": 1999,
"title": "Lecture Notes in Artificial Intelligence",
"oa_url": null,
"authors": [
"Patrick Brézillon",
"Paolo Bouquet"
],
"abstract": null,
"open_access": false,
"primary_topic": "Artificial Intelligence Applications",
"cited_by_count": 7440
},
{
"doi": "https://doi.org/10.1016/j.inffus.2019.12.012",
"year": 2019,
"title": "Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI",
"oa_url": "https://arxiv.org/pdf/1910.10045",
"authors": [
"Alejandro Barredo Arrieta",
"Natalia Díaz-Rodríguez",
"Javier Del Ser",
"Adrien Bennetot",
"Siham Tabik"
],
"abstract": null,
"open_access": true,
"primary_topic": "Explainable Artificial Intelligence (XAI)",
"cited_by_count": 8915
}
],
"generated_at": "2026-06-12T05:12:02.110Z",
"total_in_index": 2702503
}Tags
x402
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