LycheeMem vs neurostack
LycheeMem: LycheeMem is a compact memory framework for LLM agents that organizes memory into working, semantic, and procedural stores. It features a four-stage pipeline (WMManager, SearchCoordinator, SynthesizerAgent, ReasoningAgent) with a background ConsolidatorAgent, and supports multi-channel retrieval (FTS, vector, tag, temporal). It integrates via API, OpenClaw plugin, and MCP protocol.; neurostack: NeuroStack is a self-hosted MCP server and CLI that indexes Markdown vaults by meaning, providing AI agents with persistent memory across sessions. It detects stale notes, supports semantic and keyword search, and uses tiered retrieval to minimize token usage. Fully local, it never modifies your files.
TL;DR
- You are building your own agent and want a memory framework with working, semantic and procedural stores.
- You prefer light storage: SQLite with FTS5 plus a LanceDB vector index, with no Neo4j.
- You want typed, action-aware records, including a tool_affordance type for what a tool can do and when to use it.
- You want something stable today: the project has been open source only since March 2026, so APIs may change.
- You want zero extra model cost: memory extraction and retrieval use LLM and embedding calls.
- You expect the action-aware and reinforcement-learning parts to be finished: the README describes them as a direction.
Give Claude Code or other AI assistants persistent memory across sessions
Side-by-Side Comparison
LycheeMemneurostackFeatures
LycheeMemneurostackUse Cases
LycheeMemneurostackFAQ
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