M
Memori
LLM-agnostic memory infrastructure that turns agent execution and conversations into persistent state
freemiummemory-knowledge
17.0k
Stars
+315
Stars/month
5
Commits (90d)
10
Releases (6m)
Star Growth
+21 (0.1%)
Overview
Memori is an LLM-agnostic layer that turns agent execution and conversation into structured, persistent state. It integrates with existing data infrastructure and deploys across managed cloud, single-tenant cloud, VPC, and on-premises environments. The platform provides SDKs for TypeScript and Python with automatic conversation persistence and recall.
Deep Analysis
Key Differentiator
Provides agent-native memory infrastructure that works with existing data systems without requiring rip-and-replace.
⚡ Capabilities
- • persistent memory storage
- • automatic conversation recall
- • structured state management
- • LLM-agnostic integration
🔗 Integrations
OpenAITypeScript SDKPython SDKcustom databases via BYODB
✓ Best For
- ✓ enterprise agent systems
- ✓ production AI applications
- ✓ long-conversation memory management
- ✓ infrastructure integration
✗ Not Ideal For
- ✗ end-user chatbots
- ✗ image generation
- ✗ content creation tools
⚠ Known Limitations
- ⚠ requires API key setup
- ⚠ needs LLM integration
- ⚠ enterprise-focused deployment options
Alternatives
M
Mem0
Universal memory layer for AI Agents
H
Hindsight
Hindsight: Agent Memory That Learns
m
memvid
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
S
Supermemory
Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.
Works with Memori
Tools that integrate with Memori, often used together in the same stack.
Compare Memori
Maintain Memori?
Show your live rank in your README, or put Memori in front of every visitor to AgentoolRank.