MemTensor/MemOS Alternatives

Python-native memory layer with strong benchmarks as a drop-in alternative.

The best-benchmarked open-source AI memory system. And it's free.

Learning-based agent memory that improves over time, similar to self-evolving approach.

Hindsight: Agent Memory That Learns

Simple memory library for building stateful agents as a direct swap.

Memory library for building stateful agents

Universal memory layer with scalable storage and retrieval for drop-in use.

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

Very popular universal memory layer with many integrations and same approach.

Universal memory layer for AI Agents

Self-hostable memory engine with API and optional app, fully local and fast.

Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.

Team-level memory hub with governance if you already use TencentDB.

TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed, shared, and equipped across agents and frameworks.

Memory management kit with composition features as a direct alternative.

ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.

Agentic self-evolving memory, though less actively maintained.

A-MEM: Agentic Memory for LLM Agents

JVM-based cognitive memory engine if you need Java ecosystem integration.

Self-evolving cognitive memory and context engine for AI agents in Java. Empowering 24/7 proactive agents like OpenClaw with understanding and SOTA performance.

Portable SDK with framework adapters and MCP server for flexible embedding.

Portable semantic memory for AI agents: core engine, TypeScript SDK, framework adapters, MCP server, CLI, and host plugins.

Local-first, Markdown-native portable memory layer for user-owned data.

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

Agent-native memory infrastructure for production systems, LLM-agnostic.

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

Self-evolving context database unifying agent memory, RAG, and skills.

Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.

Knowledge-graph-based memory platform for persistent agent memory.

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

Benchmark-driven persistent memory optimized for coding agents.

#1 Persistent memory for AI coding agents based on real-world benchmarks

Lightweight Rust serverless memory layer when you don't need the full graph/multi-modal feature set.

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.

Session-log compression memory for simpler history injection without a graph store.

Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More