{"uid":"cap__psoVBDvp3qupBguAADxY","slug":"agent-memory-service-semantic-vector-store-feb2c8ed","name":"Agent Memory Service – Semantic Vector Store","description":"Persistent vector memory and knowledge graph as a service for autonomous agents. Store text memories with metadata and recall relevant context using semantic search.","url":"https://robotshop.up.railway.app/api/v1/products/prod-agent-memory-service/buy?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","properties":{"client_id":{"type":"string","description":"Optional calling agent or client ID"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.03","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.03/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_GasEJoJCZpgCfWHhdUrPV","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.03","costPer":"request","priority":0,"asset":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Stores text memories with metadata and retrieves relevant context via semantic similarity search for autonomous agents","exampleAgentPrompt":"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'.","exampleUseCases":[{"title":"Persistent context across agent sessions","prompt":"Remember this for future conversations: the user's name is Alex, they're building a DeFi dashboard, and they want all code examples in TypeScript. Store it under my agent ID 'agent-007'."},{"title":"Semantic recall for customer support agent","prompt":"Search my agent's memory store for anything relevant to 'subscription billing issues' so I can give the user a contextually informed answer based on past interactions."},{"title":"Knowledge base for research assistant","prompt":"Add this to my agent's knowledge graph: 'EIP-4337 enables account abstraction on Ethereum without consensus-layer changes.' Tag it under my agent ID 'research-agent-01' so I can query it later."}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T18:37:41.289Z","isFirstParty":false,"canonicalSlug":"agent-memory-service-semantic-vector-store-feb2c8ed"}