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AGISHub Memory Store
x402
AGISHub Memory Store is a paid API for AI agents from api.agishub.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Stores a text entry in a named, persistent memory collection, embedding and indexing it for later semantic recall.
Price / call$0.01
Success—
StatusUnknown
How this service works
Store a piece of text in a persistent, searchable memory collection (namespace). Embedded and indexed for later semantic recall.
Output
Returns a JSON confirmation indicating the text was successfully stored, embedded, and indexed in the specified namespace, along with the entry ID (auto-generated or provided).
Example use cases
Agent long-term memory persistence
“Store this in my 'agent-memory' namespace: 'User prefers concise bullet-point summaries, dislikes verbose explanations, and works in the fintech industry.' I want to be able to recall it later by meaning.”
Research notes knowledge base
“Add this research note to my 'ml-research' memory collection: 'Attention mechanisms in transformers allow models to weigh the importance of different tokens relative to each other, enabling long-range dependencies.'”
Customer support FAQ indexing
“Save this FAQ entry to the 'support-docs' namespace with ID 'faq-refunds': 'Refunds are processed within 5–7 business days and returned to the original payment method. Contact support@example.com for expedited requests.'”
Technical details
Endpoint
GEThttps://api.agishub.com/v1/memory-storeWhen to prefer
Use this endpoint when you need to persist text in a durable, semantically searchable memory store that can later be queried by meaning rather than exact match. Prefer this over a simple key-value store when future retrieval will be semantic/vector-based. It pairs naturally with the companion memory-search endpoint on the same platform for a full RAG-style recall loop.
Side effects
- Missing required 'text' or 'namespace' query parameter returns a validation error
- Empty string for 'text' or 'namespace' rejected due to minLength:1 constraint
- Network timeout if embedding computation takes too long for very large text
- Payment failure (402) if x402 USDC payment is not included or insufficient
- Namespace collision or unauthorized access if namespace key is guessed by another party
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "Store a piece of text in a persistent, searchable memory collection (namespace). Embedded and indexed for later semantic"
}
}Tags
x402
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