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Macaroon Network Scientific Dataset Search
x402
Macaroon Network Scientific Dataset Search is a paid API for AI agents from api.macaroonnetwork.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Search an indexed corpus of scientific datasets by topic and retrieve structured metadata pointers, licence declarations, provenance, and freshness information without downloading the actual data files.
Price / call$0.002
Success—
StatusUnknown
How this service works
Find source-linked scientific datasets by topic. Returns structured metadata pointers, declared licence fields, provenance and freshness without redistributing dataset files.
Output
Structured metadata records for matching scientific datasets, including source URLs linking back to the original host, declared licence fields (e.g. CC BY, public domain), provenance details indicating dataset origin, and freshness indicators showing when the data was last indexed or updated. Actual dataset files are not transferred or redistributed.
Example use cases
Academic research data discovery
“Find me scientific datasets about CRISPR gene editing — I need to know their sources, what licences they're under, and when they were last updated so I can cite them properly in my paper.”
ML training data sourcing
“I'm training a model on satellite imagery of deforestation — can you search for openly licensed scientific datasets on that topic and show me their provenance and metadata without downloading them?”
Policy brief background research
“Search for peer-linked datasets on urban air quality and particulate matter across major cities — I need the licence terms and source information to confirm they're usable for a public health policy report.”
Technical details
Endpoint
POSThttps://api.macaroonnetwork.com/execute/polymathica-scientific-dataset-search-v1When to prefer
Choose this endpoint when an agent needs to discover scientific datasets by topic without downloading or redistributing actual data files. It is ideal for research workflows requiring licence verification, provenance auditing, or freshness checks before committing to a dataset. Prefer it over generic web search when structured, source-linked metadata is needed, and over data repositories' own APIs when aggregating across multiple domains in a single call.
Side effects
- No matching datasets found for the query topic — returns empty result set
- Overly broad query terms may return a large unfiltered list requiring further refinement
- Dataset metadata may be stale if the underlying source has changed since last index crawl
- Ambiguous topic queries may surface tangentially related datasets from adjacent fields
- Payment processing failure returns 402 before any search is executed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"payload": {
"query": "",
"total": 0,
"records": [],
"provenance": {
"content_hash": null,
"metadata_only": null,
"no_outbound_network_on_purchase": null
}
},
"settled": true,
"predicate_passed": true
}
}Tags
x402
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