SignalDesk AI Crossref Academic Search

x402

SignalDesk AI Crossref Academic Search is a paid API for AI agents from x402-agent.kariguetoazul.workers.dev, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-12).

Searches the Crossref scholarly database for academic publications matching a text query, returning DOIs, titles, authors, citations, and publisher metadata.

Price / call$0.003

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StatusUnknown

How this service works

Evidence-backed autonomous AI jobs and paid data tools. Queue/D1/cron run outside the chat; free quotas and bounded execution apply.

Output

Returns a JSON object with the total number of matching records in Crossref, metadata about the data source (provider, fetch time, expiry, source URL), and an array of result objects each containing DOI, URL, document type, publication year, title, list of authors, citation count, publisher, and optional license information.

Example use cases

Academic literature review for research

“Find me the 10 most relevant Crossref publications about CRISPR gene editing so I can start building a literature review — I need titles, authors, DOIs, and citation counts.”

Fact-checking a citation in a report

“I need to verify a citation — can you search Crossref for 'reinforcement learning reward shaping' and pull up the top results with their DOIs and publishers so I can check if a specific paper exists?”

Discovering recent works on a niche topic

“Search Crossref for academic papers on 'antibiotic resistance in soil microbiomes' and return up to 8 results with their publication years and authors.”

Technical details

Endpoint

GEThttps://x402-agent.kariguetoazul.workers.dev/api/research/crossref-search?utm_source=zero.xyz

When to prefer

Use this endpoint when you need structured scholarly metadata from Crossref — including DOIs, citation counts, authors, and publisher info — for a natural language keyword query. Prefer this over direct Crossref API calls when you need a ready-transformed JSON response with bounded cost per query via x402 micropayment. Best for literature discovery, citation verification, and academic research workflows.

Side effects

Empty query string or missing required 'q' parameter returns a validation error
Query exceeding 200 characters is rejected
Limit parameter outside 1–20 range is rejected
Crossref upstream API unavailability causes a 502 or timeout
No results found for highly specific or misspelled queries returns empty results array
Rate limiting or quota exhaustion from the paid x402 tier

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "type": "json",
  "example": {
    "total": 3036540,
    "source": {
      "provider": "Crossref metadata",
      "expires_at": "2026-10-02T10:44:49.355Z",
      "fetched_at": "2026-10-02T09:44:49.355Z",
      "source_url": "https://api.crossref.org/works?query=machine%20learning&rows=3",
      "transformed": true
    },
    "results": [
      {
        "doi": "10.1093/oso/9780198828044.003.0003",
        "url": "https://doi.org/10.1093/oso/9780198828044.003.0003",
        "type": "book-chapter",
        "year": 2019,
        "title": "Machine learning with sklearn",
        "authors": [
          {
            "given": "Thomas P.",
            "family": "Trappenberg"
          }
        ],
        "cited_by": 19,
        "publisher": "Oxford University Press"
      },
      {
        "doi": "10.1002/9781119902881",
        "url": "https://doi.org/10.1002/9781119902881",
        "type": "monograph",
        "year": 2022,
        "title": "Optimization and Machine Learning",
        "authors": [],
        "cited_by": 1,
        "licenses": [
          {
            "URL": "http://doi.wiley.com/10.1002/tdm_license_1.1",
            "start": {
              "date-time": "2022-02-25T00:00:00Z",
              "timestamp": 1645747200000,
              "date-parts": [
                [
                  2022,
                  2,
                  25
                ]
              ]
            },
            "delay-in-days": 0,
            "content-version": "tdm"
          }
        ],
        "publisher": "Wiley"
      },
      {
        "doi": "10.1017/cbo9780511804779.017",
        "url": "https://doi.org/10.1017/cbo9780511804779.017",
        "type": "book-chapter",
        "year": 2012,
        "title": "Machine learning",
        "authors": [],
        "cited_by": 1,
        "licenses": [
          {
            "URL": "https://www.cambridge.org/core/terms",
            "start": {
              "date-time": "2012-06-05T00:00:00Z",
              "timestamp": 1338854400000,
              "date-parts": [
                [
                  2012,
                  6,
                  5
                ]
              ]
            },
            "delay-in-days": 0,
            "content-version": "unspecified"
          }
        ],
        "publisher": "Cambridge University Press"
      }
    ]
  }
}

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