A local SQLite-backed memory layer that gives any LLM agent persistent context about the user's projects, preferences, and history across sessions without sending data to the cloud
Every cloud AI agent starts from zero context each session. OpenHuman proved the demand is real by hitting 26.8k GitHub stars and #1 on both GitHub Trending and Product Hunt in a single week with its local-first memory approach. But OpenHuman is a full agent framework. Most developers already have an agent they like (Claude Code, Cursor, Copilot) and just want the memory part. This is a standalone memory layer that plugs into any agent via a simple API, stores structured context locally in SQLite, and makes the user's full history available to every prompt without cloud dependency.
Demand Breakdown
Social Proof 1 sources
Gap Assessment
3 tools exist (OpenHuman, Mem0, Letta (MemGPT)) but gaps remain: It is a complete agent framework, not a pluggable memory layer. Cannot be used with existing agents like Claude Code or Cursor. All-or-nothing adoption.; Cloud-first architecture. Self-hosted option requires running a separate server. Not a simple local-only SQLite file..
Features3 agent-ready prompts
Competitive LandscapeFREE
| Product | Does | Missing |
|---|---|---|
| OpenHuman | Full desktop AI agent with local memory tree, 118+ OAuth integrations, voice features, and meeting agent | It is a complete agent framework, not a pluggable memory layer. Cannot be used with existing agents like Claude Code or Cursor. All-or-nothing adoption. |
| Mem0 | Memory layer for AI agents with cloud and self-hosted options | Cloud-first architecture. Self-hosted option requires running a separate server. Not a simple local-only SQLite file. |
| Letta (MemGPT) | Stateful LLM agents with long-term memory management | Server-based architecture. Focused on building new agents, not adding memory to existing ones. Heavier setup. |
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