Mnemosyne
Local-first memory system for AI agents, SQLite-backed, zero dependencies
Visit mnemosyne.site ↗What is Mnemosyne?
Mnemosyne is a memory layer designed for AI agents that runs entirely locally using SQLite, requiring only a single Python dependency and one pip install. It offers sub-millisecond query latency, stores data locally without cloud services or API keys, and integrates with multiple agent frameworks including Cursor, Claude Code, OpenWebUI, and any MCP-compatible client.
The system manages episodic memories, summaries, and knowledge graphs through a browser-based demo or direct Python SDK. It supports negation extraction, instruction parsing, and memory consolidation. The project is open source and available on OpenCollective, with active development tracked on GitHub.
Momentum
Daily activity over the last 30 days: upvotes, unique visits, new GitHub stars and Hacker News points.
How do we know it's vibe coded?
vibetrend discovered Mnemosyne automatically. Evidence: GitHub mnemosyne-oss/mnemosyne; repo has .claude. View source.
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