plastic-labs/honcho Alternatives

Choose when you want a permissively Apache-2.0 licensed drop-in memory layer with broad production SDK support.

Universal memory layer for AI Agents

Choose when you prefer an MIT-licensed, benchmark-focused memory system over Honcho's AGPL service.

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

Choose when you want a self-contained MIT Python memory library that learns continuously without a standalone server.

Hindsight: Agent Memory That Learns

Choose when you need an Apache-2.0 memory management kit with explicit tiered memory abstractions for agent orchestration.

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

Choose when you want an Apache-2.0 universal memory layer with pluggable storage backends rather than a self-hosted Python service.

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.

Choose when you need a locally runnable TypeScript memory API with a permissive MIT license and a bundled management app.

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

Choose when you need an enterprise-hardened, LLM-agnostic memory infrastructure with structured persistent state.

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.

Choose when you want local-first, Markdown-native, user-owned memory under Apache-2.0 instead of an AGPL cloud-capable service.

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

Choose when you need a lightweight Rust/WASM serverless memory layer instead of a Python FastAPI service.

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.

Choose when your agents run on the JVM and you need an in-process Java memory engine rather than calling a Python service.

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

Choose when you want a TypeScript-native portable memory core with MCP/CLI adapters and no Python runtime dependency.

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

Choose when you need team-governed memory assets (chat, skill, wiki, code-graph) on TencentDB rather than a raw memory service.

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.

Choose when you want a self-evolving memory OS with skill reuse and token-saving hybrid retrieval beyond Honcho's event-based model.

Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.

Choose when you want a context database that unifies agent memory, knowledge RAG, and skills under AGPL instead of a pure memory library.

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

Choose when you prefer a knowledge-graph-backed memory platform over Honcho's event/session and vector-style memory views.

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.

Choose when you are already on Milvus and want a Markdown-backed unified memory server for multiple coding-agent CLIs.

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.

Choose when you need an MCP-friendly REST memory server with knowledge-graph consolidation for LangGraph/CrewAI/AutoGen pipelines.

Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.

Choose when you want a visual, rollbackable MCP memory server with graph-like memories and no vector RAG.

A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, session, or tool. Drop-in replacement for OpenClaw.

Choose when you are building a TypeScript coding agent and want a lightweight memory library tuned to coding workflows and benchmarks.

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

Choose when you want a research implementation of agentic memory for benchmarking/experiments rather than a maintained production service.

A-MEM: Agentic Memory for LLM Agents

Choose when you use Claude Code/Codex and want drop-in session memory capture/reinjection with no custom integration code.

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

Choose when you want a local memory server for existing desktop/IDE agents (Claude Desktop, Copilot, Codex) rather than an API for custom agents.

Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.

Choose when you use CortexKit-based coding agents and want a self-managing context/memory layer without wiring your own agent integration.

Unbounded context. Memory that manages itself. One session, for life. The hippocampus for coding agents, part of CortexKit.

Choose when you want a local personal memory engine that plugs into Cursor/Claude Code/Codex instead of integrating memory into your own agent code.

A cyber brain for your AI. It never forgets a detail, remembers exactly what you said, and learns how you work over time. Free, local, works with Cursor, Claude Code, Codex, OpenClaw, Hermes and more. MIT.