# Agent Memory Service – Semantic Vector Store

> Agent Memory Service – Semantic Vector Store is a paid API for AI agents from robotshop.up.railway.app, paid per call via x402, $0.03/call, status unknown (last checked 2026-10-12).

Stores text memories with metadata and retrieves relevant context via semantic similarity search for autonomous agents

## Facts

- Endpoint: GET https://robotshop.up.railway.app/api/v1/products/prod-agent-memory-service/buy?utm_source=zero.xyz
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agent-memory-service-semantic-vector-store-feb2c8ed
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap__psoVBDvp3qupBguAADxY

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability agent-memory-service-semantic-vector-store-feb2c8ed
```

Example prompt: Save this to my persistent agent memory so I can recall it later: 'The user prefers concise bullet-point responses and works in fintech' — tag it with client_id 'agent-007'.

## When to prefer this

Choose this endpoint when your agent needs persistent, semantically searchable memory across sessions — especially when simple key-value storage is insufficient and you need fuzzy recall based on meaning rather than exact keys. Ideal for long-running autonomous agents that accumulate context over time and need to surface relevant past knowledge dynamically.

## Known failure modes

- Invalid or missing client_id may result in anonymous or unscoped memory storage
- Semantic search may return low-relevance results if memory store is sparse
- Network timeout if the vector index is under heavy load
- Payment failure (x402) if USDC balance is insufficient — returns 402 status
- Memory not found if the store has been purged or TTL expired

## How this service works

Persistent vector memory and knowledge graph as a service for autonomous agents. Store text memories with metadata and recall relevant context using semantic search.

## Output

Returns stored memory entries or semantically relevant recalled memories matching the query context, enabling agents to maintain persistent state and retrieve previously stored knowledge across sessions.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "client_id": {
   "type": "string",
   "description": "Optional calling agent or client ID"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agent-memory-service-semantic-vector-store-feb2c8ed/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from robotshop.up.railway.app](https://www.zero.xyz/host/robotshop.up.railway.app/llms.txt)