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Use when wiring mem0() from @tanstack/ai-memory/mem0 — a hosted memory adapter that talks to a mem0 server over plain HTTP (no SDK peer). Requires a running mem0 server.
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Use when wiring hindsight() from @tanstack/ai-memory/hindsight — a hosted memory adapter that buckets memory per conversation and exposes retain/recall/reflect tools to the model. Requires the optional @vectorize-io/hindsight-client peer.
Use when wiring honcho() from @tanstack/ai-memory/honcho — a hosted memory adapter where recall is a dialectic answer over the user's representation (no discrete fragments). Requires the optional @honcho-ai/sdk peer.
Use when wiring redis() from @tanstack/ai-memory/redis in production — covers client setup (ioredis or node-redis via fromNodeRedis), the storage model, client-side ranking limits, and troubleshooting.
Use when wiring memoryMiddleware from @tanstack/ai-memory into a chat() call — covers the recall/save adapter contract, scope shape and server-side scope security, the recall-inject / deferred-save lifecycle, choosing an adapter (inMemory, redis, hindsight, mem0, honcho), and devtools events.
Use when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent).
Entry point for TanStack AI skills. Routes to chat-experience, tool-calling, media-generation, structured-outputs, adapter-configuration, ag-ui-protocol, middleware, custom-backend-integration, and debug-logging. Use chat() not streamText(), openaiText() not createOpenAI(), toServerSentEventsResponse() not manual SSE, middleware hooks not onEnd callbacks.
| name | tanstack-ai-memory-mem0 |
| description | Use when wiring mem0() from @tanstack/ai-memory/mem0 — a hosted memory adapter that talks to a mem0 server over plain HTTP (no SDK peer). Requires a running mem0 server. |
Hosted recall/save adapter backed by a mem0 server. mem0 owns extraction and ranking
server-side. Talks to the server over plain HTTP — no SDK peer dependency.
import { memoryMiddleware } from '@tanstack/ai-memory'
import { mem0 } from '@tanstack/ai-memory/mem0'
const memory = mem0({ user: currentUserId }) // baseUrl defaults to MEM0_URL
memoryMiddleware({ adapter: memory, scope })
Requires a running mem0 server (self-hosted or hosted). Point it via baseUrl (or
MEM0_URL); pass apiKey (or MEM0_ADMIN_API_KEY) when secured.
user — mem0 user_id (falls back to scope.userId, then 'demo-user').baseUrl — mem0 server URL (default MEM0_URL or http://localhost:8000).apiKey — bearer token (default MEM0_ADMIN_API_KEY).rerank (default true), threshold (default 0.1) — search tuning.Scope fields: requests send user_id and run_id (scope.threadId). tenantId
and namespace are not sent — encode multi-tenant isolation into user if needed.
save posts the { user, assistant } turn to /memories; recall queries /search
and renders the results into the system prompt. mem0 exposes no LLM tools.