claude-mem vs supermemory
Cross-harness session memory: hooks capture what the agent does, an LLM compresses it into observations, and the next session gets the relevant ones back via progressive-disclosure MCP tools. — versus — Memory and context engine for AI: fact extraction, user profiles, contradiction handling and forgetting, hybrid RAG + memory search, connectors, agent plugins and a one-binary local mode.
For Claude Code specifically: claude-mem compresses the agent's own sessions into observations, Supermemory's plugin keeps preferences and project facts in a memory API shared across tools.
| claude-mem | supermemory | |
|---|---|---|
| Stars | 95k | 31k |
| Forks | 8.4k | 2.7k |
| Language | JavaScript | TypeScript |
| License | Apache-2.0 | MIT |
| Last activity | yesterday | today |
| Topics | memory, coding | memory, rag |
| Curated connections | 9 | 4 |
claude-mem — the curator's take
The most widely installed of the capture-and-reinject memory plugins, and the one with the most product around it: 5 lifecycle hooks, a Bun worker with an HTTP API and live web viewer, SQLite plus FTS5 plus Chroma for hybrid search, and a 3-layer MCP search pattern (index → timeline → full detail) that keeps recall at ~50-100 tokens per hit until you actually want the body. Installs into Claude Code, OpenCode, Antigravity, OpenClaw and more, with `<private>` tags to keep things out of the store and optional cloud sync. The tradeoffs: it spends model tokens summarizing every session, it drags in Bun and uv, and what you get back is a generated observation rather than the raw transcript — if you want auditable, greppable memory you can edit by hand, look at the Markdown-first options instead.
supermemory — the curator's take
The most complete memory product on the map: fact extraction with temporal updates and forgetting, ~50ms user profiles, RAG and memory in one query, connectors for Drive, Gmail, Notion and GitHub, and plugins for Claude Code, Codex, Cursor, OpenCode and Hermes. `npx supermemory local` runs the same Memory API on your machine with local embeddings, so prototyping does not need their cloud; connectors are not in the local feature list, so check before planning around them. Treat the '#1 on every benchmark' banner as vendor-reported. Skip it if you want memory you can read and edit as files (acontext, okf-agent-memory) or only need session recall for one coding agent.