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Macaroon Network Scientific ML Model Search
x402
Macaroon Network Scientific ML Model 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 open-science repositories for scientific machine-learning model records by topic, returning metadata and provenance pointers without downloading weights.
Price / call$0.002
Success—
StatusUnknown
How this service works
Find source-linked scientific machine-learning model records by topic. Returns metadata and provenance pointers only; model weights are not downloaded or resold, and missing licence evidence remains unknown.
Output
Returns a list of scientific ML model records matching the topic query, each with metadata (model name, description, topic tags), provenance pointers (source repository URLs, paper links), and available licence information. Model weights are not included. Records with unknown licence evidence are flagged as such.
Example use cases
Discovering genomics ML models
“Find me scientific ML model records related to genomic sequence analysis — I need their provenance, where they came from, and any licence details you can surface.”
Auditing open-science model provenance
“I'm vetting models for a research project on material property prediction. Can you search for scientific ML models on that topic and pull back their source links and provenance so I can check where they originated?”
Exploring drug discovery AI models
“Search for machine learning models used in drug discovery or molecular docking and give me the metadata and source pointers for whatever you find in the open-science corpus.”
Technical details
Endpoint
POSThttps://api.macaroonnetwork.com/execute/polymathica-scientific-model-search-v1When to prefer
Use this endpoint when an agent needs to discover scientific ML models by topic, obtain their provenance and source links, or audit model origins within the open-science ecosystem. Prefer this over general web search when structured, source-linked metadata is needed. Not suitable for downloading model weights or executing models — use the GPU job submission sibling endpoint for that.
Side effects
- No records found for highly niche or non-standard topic queries
- Licence information may be absent or unknown for many models
- Results are bounded to the indexed snapshot and may not include very recent models
- Ambiguous or overly broad queries may return low-relevance results
- Malformed request body returns validation error
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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