Mneme is a standalone memory system for AI agents that installs as a single binary with no cloud or database setup required. It runs entirely offline with built-in encryption, works with every major AI coding assistant and agent framework, and offers 46 tools for storing, searching, and managing persistent memory—making it the only option that combines MCP-native design, local-first operation, and zero external dependencies according to its comparison matrix.
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Mneme, a lightweight memory engine for AI agents, launched as a single Rust binary (~8MB) with no external dependencies—just SQLite embedded. It works with any MCP host (Claude Desktop, Cursor, Hermes Agent, and seven others) and includes 46 MCP tools for storing, searching, and managing persistent agent memory across sessions.
Why it matters
Unlike competitors (Mem0, Letta, Zep), Mneme runs entirely local and offline, with AES-256-GCM encryption built in. For developers and organizations handling sensitive agent workflows, this removes cloud dependency and data-residency concerns. It integrates with LangGraph, CrewAI, and AutoGen, making it straightforward to plug into existing AI agent frameworks.
What to watch
Stress testing shows Mneme handles 100K entities at ~98,732 insertions/second, using ~85MB memory and a ~45MB database file. Install is one-line (curl command), and the tool offers hybrid search (BM25 + dense vectors + reciprocal-rank fusion), entity lifecycle management, and an immutable audit trail—features the comparison matrix shows absent from all three named competitors.
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