MemoriLabs/Memori

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

16241 stars · 3254 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Memori is agent-native memory infrastructure that turns LLM agent execution and conversation into structured, persistent state. It ships as Python and TypeScript SDKs with a managed cloud or self-hosted BYODB deployment, and is LLM, datastore, and framework agnostic.

Use cases

• give my ai agent long-term memory across conversations
• persist agent state in production llm apps
• remember user preferences and facts from chat automatically
• add memory to claude code or openai agents
• reduce token usage when recalling conversation context
• self-host agent memory with my own database
• semantic recall of past conversations for a chatbot

When to choose

• you need production-grade, persistent memory for LLM agents with enterprise deployment options (VPC, on-prem)
• you want LLM- and datastore-agnostic memory that works with your existing stack
• you need explainable, traceable memory recall with audit logging and access control

When to avoid

• you only need simple in-process session state with no persistence
• you want a fully open-source solution without any cloud dependency or API key
• your project is not agent- or LLM-based

Facets

library · maturity active

rag agent-framework state-management llm-inference database sdk artificial-intelligence large-language-models developer-tools python cross-platform self-hosted cloud agent-memory memory-infrastructure llm-agnostic enterprise mcp-server conversation-memory byodb ai-agents retrieval-augmented-generation nodejs

Member repositories

For agents

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