{"uid":"cap_QLb6AUIoosFNL0wB2nCcs","slug":"agishub-memory-search-18b37e81","name":"AGISHub Memory Search","description":"Semantically search a memory collection (namespace) and return the most relevant stored entries. The retrieval half of RAG.","url":"https://api.agishub.com/v1/memory-search","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input","output"],"properties":{"input":{"type":"object","required":["type","method","queryParams"],"properties":{"type":{"enum":["http"],"type":"string"},"method":{"enum":["GET"],"type":"string"},"queryParams":{"type":"object","required":["namespace","query"],"properties":{"query":{"type":"string","minLength":1,"description":"Natural-language query; returns the most semantically similar stored entries."},"top_k":{"type":"integer","maximum":20,"minimum":1,"description":"How many results to return (default 5)."},"namespace":{"type":"string","minLength":1,"description":"The namespace to search within (the same key used on upsert)."}},"additionalProperties":false}},"additionalProperties":false},"output":{"type":"object","required":["type","example"],"properties":{"type":{"enum":["json"],"type":"string"},"example":{"type":"object"}},"additionalProperties":false}}},"responseSchema":{"type":"json","example":{"result":"Semantically search a memory collection (namespace) and return the most relevant stored entries. The retrieval half of R"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Y0PvJX57B7fu0-ttVV5Eo","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Semantically searches a named memory namespace and returns the most relevant stored entries using vector similarity — the retrieval step of a RAG pipeline.","exampleAgentPrompt":"Search my 'customer-support' namespace for the top 3 entries most similar to 'how do I reset my password?' and return what you find.","exampleUseCases":[{"title":"RAG context retrieval for chatbot","prompt":"Search the 'product-docs' namespace for the 5 most relevant stored chunks matching the question 'what are the system requirements for installation?' so I can augment my answer."},{"title":"Personal knowledge base recall","prompt":"Look in my 'personal-notes' namespace for anything semantically related to 'annual budget planning' — give me the top 3 results."},{"title":"Agent memory lookup before responding","prompt":"Before you reply to this user, search the 'conversation-history' namespace for the top 5 entries most similar to 'user's dietary preferences' so you can personalize the response."}],"resultDescription":"Returns a ranked list of the most semantically similar stored entries from the specified namespace, ordered by relevance to the query. The number of results is controlled by top_k (default 5, max 20).","failureModes":["Namespace not found — returns empty results or error if the namespace hasn't been populated","Query too short or empty — rejected due to minLength:1 validation","top_k out of range — rejected if below 1 or above 20","No matching entries — returns empty results if no stored content is semantically close to the query","Network timeout — if the vector search backend is slow or unavailable"],"whenToPreferThis":"Use this endpoint when you need to retrieve the most semantically relevant stored entries from a named memory namespace as part of a RAG pipeline or agent memory recall loop. It is specifically designed for the retrieval step — prefer it over generic full-text search when you need similarity-ranked results based on meaning rather than keyword overlap. Ideal when entries were upserted via the paired memory upsert endpoint on the same platform.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T18:55:54.668Z","isFirstParty":false}