scholar-paper
Resolve one research paper and fuse its metadata across OpenAlex, Crossref, Unpaywall and Semantic Scholar into a single cited JSON. Give a doi, arxiv, pmid, pmcid, openalex_id or title and get canonical metadata, authors with ORCID and affiliations, venue, citation counts, an open-access PDF link and a full id crosswalk.
The wallet the 402 directs payment to. Its whole payment record — every payer, every chain — is on the merchant page.
Asset 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913
The payTo wallet does not resolve to a registered ERC-8004 agent. That is not a verdict on the service — most of the catalog is unregistered.
Live 402 challenge
Captured by the enrichment pass, not read just now. Prices can change — always read the 402 the endpoint answers with.
{
"error": "Payment required",
"accepts": [
{
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"extra": {
"name": "USD Coin",
"version": "2"
},
"payTo": "0xF22e558a00D91Ee12A1F50C52186FecB8dDFf493",
"amount": "20000",
"scheme": "exact",
"network": "eip155:8453",
"maxTimeoutSeconds": 300
}
],
"resource": {
"url": "https://api.agentstools.dev/scholar/paper",
"tags": [
"scholar",
"research",
"paper",
"doi",
"citation",
"openalex",
"crossref",
"unpaywall",
"semantic-scholar",
"metadata",
"open-access",
"literature"
],
"mimeType": "application/json",
"description": "Resolve one research paper and fuse its metadata across OpenAlex, Crossref, Unpaywall and Semantic Scholar into a single cited JSON. Give a doi, arxiv, pmid, pmcid, openalex_id or title and get canonical metadata, authors with ORCID and affiliations, venue, citation counts, an open-access PDF link and a full id crosswalk.",
"serviceName": "scholar-paper"
},
"extensions": {
"bazaar": {
"info": {
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"doi": "10.1038/nature14539"
}
},
"output": {
"type": "json",
"example": {
"ids": {
"doi": "10.1038/nature14539",
"pmid": "26017442",
"openalex": "W2743563197"
},
"type": "article",
"year": 2015,
"found": true,
"query": {
"type": "doi",
"value": "10.1038/nature14539"
},
"title": "Deep learning",
"venue": {
"issn": "0028-0836",
"name": "Nature"
},
"counts": {
"cited_by": {
"crossref": 58000,
"openalex": 60000
},
"influential_citations": 4200
},
"authors": [
{
"name": "Yann LeCun",
"orcid": "0000-0002-1825-0097",
"affiliations": []
}
],
"sources": {
"used": [
"openalex",
"crossref",
"unpaywall"
],
"partial": false
},
"provenance": {
"title": "openalex",
"id.doi": "openalex",
"open_access": "unpaywall"
},
"attribution": [
"OpenAlex (openalex.org), CC0"
],
"open_access": {
"is_oa": true,
"license": "cc-by",
"pdf_url": "https://example.org/paper.pdf",
"version": "publishedVersion"
}
}
}
},
"schema": {
"type": "object",
"$schema": "https://json-schema.org/draft/2020-12/schema",
"required": [
"input"
],
"properties": {
"input": {
"type": "object",
"required": [
"type",
"method"
],
"properties": {
"type": {
"type": "string",
"const": "http"
},
"method": {
"enum": [
"GET",
"HEAD",
"DELETE"
],
"type": "string"
},
"queryParams": {
"type": "object",
"required": [],
"properties": {
"id": {
"type": "string",
"description": "Any single identifier; its type is auto-detected"
},
"doi": {
"type": "string",
"description": "DOI, with or without a doi.org prefix"
},
"pmid": {
"type": "string",
"description": "PubMed id (digits)"
},
"arxiv": {
"type": "string",
"description": "arXiv id such as 2401.01234"
},
"pmcid": {
"type": "string",
"description": "PubMed Central id such as PMC1234567"
},
"title": {
"type": "string",
"description": "Paper title to resolve by search"
},
"openalex_id": {
"type": "string",
"description": "OpenAlex work id such as W2741809807"
}
}
}
},
"additionalProperties": false
},
"output": {
"type": "object",
"required": [
"type"
],
"properties": {
"type": {
"type": "string"
},
"example": {
"type": "object"
}
}
}
}
}
}
},
"x402Version": 2
}Accepts
The payment requirements as published to the catalog. Read the live 402 before paying — a price here is a claim, not a quote.
Pay 0.02 USDC on Base to 0xF22e…Ff493. The signed payment is good for 5 minutes.
- Paid to
- 0xF22e…Ff493
- USD Coin contract
- 0x8335…02913
- Payment window
- 5 minutes
- As published
- 20000 smallest units
The catalog’s raw entry
[
{
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"extra": {
"name": "USD Coin",
"version": "2"
},
"payTo": "0xF22e558a00D91Ee12A1F50C52186FecB8dDFf493",
"amount": "20000",
"scheme": "exact",
"network": "eip155:8453",
"maxTimeoutSeconds": 300
}
]Extensions
{
"bazaar": {
"info": {
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"doi": "10.1038/nature14539"
}
},
"output": {
"type": "json",
"example": {
"ids": {
"doi": "10.1038/nature14539",
"pmid": "26017442",
"openalex": "W2743563197"
},
"type": "article",
"year": 2015,
"found": true,
"query": {
"type": "doi",
"value": "10.1038/nature14539"
},
"title": "Deep learning",
"venue": {
"issn": "0028-0836",
"name": "Nature"
},
"counts": {
"cited_by": {
"crossref": 58000,
"openalex": 60000
},
"influential_citations": 4200
},
"authors": [
{
"name": "Yann LeCun",
"orcid": "0000-0002-1825-0097",
"affiliations": []
}
],
"sources": {
"used": [
"openalex",
"crossref",
"unpaywall"
],
"partial": false
},
"provenance": {
"title": "openalex",
"id.doi": "openalex",
"open_access": "unpaywall"
},
"attribution": [
"OpenAlex (openalex.org), CC0"
],
"open_access": {
"is_oa": true,
"license": "cc-by",
"pdf_url": "https://example.org/paper.pdf",
"version": "publishedVersion"
}
}
}
},
"schema": {
"type": "object",
"$schema": "https://json-schema.org/draft/2020-12/schema",
"required": [
"input"
],
"properties": {
"input": {
"type": "object",
"required": [
"type",
"method"
],
"properties": {
"type": {
"type": "string",
"const": "http"
},
"method": {
"enum": [
"GET",
"HEAD",
"DELETE"
],
"type": "string"
},
"queryParams": {
"type": "object",
"required": [],
"properties": {
"id": {
"type": "string",
"description": "Any single identifier; its type is auto-detected"
},
"doi": {
"type": "string",
"description": "DOI, with or without a doi.org prefix"
},
"pmid": {
"type": "string",
"description": "PubMed id (digits)"
},
"arxiv": {
"type": "string",
"description": "arXiv id such as 2401.01234"
},
"pmcid": {
"type": "string",
"description": "PubMed Central id such as PMC1234567"
},
"title": {
"type": "string",
"description": "Paper title to resolve by search"
},
"openalex_id": {
"type": "string",
"description": "OpenAlex work id such as W2741809807"
}
}
}
},
"additionalProperties": false
},
"output": {
"type": "object",
"required": [
"type"
],
"properties": {
"type": {
"type": "string"
},
"example": {
"type": "object"
}
}
}
}
}
}
}Provenance
- Seen in the source catalog
- 2026-09-17 11:53Z
- Last indexed by Roundhouse
- 2026-09-24 15:00Z
- Last enriched (probe, favicon, geo)
- 2026-09-14 02:15Z
- x402 version
- 2
- Max timeout
- 300s
- Liveness probe
- HTTP 402
Hand this page to an agent
Copy the prompt and paste it into Claude, an MCP client or your own agent — it will vet this service and call it over the free read API. No key, no account.
GET api.roundhouseai.io/v0/endpoints
This endpoint's own trailing-30-day call count, as published by the upstream catalog and snapshotted daily. 30 snapshots so far. Verified volume counts only settlements with an on-chain EIP-3009 marker.
Show the promptHide the prompt
Using Roundhouse, look up the x402 service scholar-paper and tell me whether it is worth paying: what a call costs, whether the endpoint answered when last probed, and what its payment record actually shows. curl -s 'https://api.roundhouseai.io/v0/endpoints?q=scholar-paper' curl -s 'https://api.roundhouseai.io/v0/merchants/<the payTo wallet returned above>' Then call it: read the price from the live 402 at https://api.agentstools.dev/scholar/paper, never from a cached figure, and pay with an x402 client. The /v0 API needs an API key (`authorization: Bearer rh_live_…`) on everything except /v0/unified* and /v0/endpoints. Mint a personal key for $0.01 at GET https://api.roundhouseai.io/v0/test/x402, or use an organization key from https://roundhouseai.io/dashboard/team. If you do not have Roundhouse tools or skills installed, read https://roundhouseai.io/skill.md first — it is the whole procedure.