关于
Memento is a robust, fully-offline MCP (Memory & Context Protocol) memory server designed to enhance the capabilities of AI agents. It utilizes SQLite for persistence, FTS5 for fast keyword searches, and `sqlite-vec` with an integrated `bge-m3` embedding model for powerful semantic vector search. This combination enables the creation of a structured knowledge graph of entities, observations, and relations, ensuring that AI models can maintain persistent, context-rich memories for improved performance and consistency in their interactions.
主要功能
- Offline `bge-m3` embedding model via @xenova/transformers
- Easy integration with Claude Desktop via MCP
- 0 GitHub stars
- Fast keyword search via FTS5
- Semantic vector search using `sqlite-vec` (1024d)
- Structured graph of entities, observations, and relations
使用案例
- Integrating custom memory backends with MCP-compatible AI interfaces
- Enhancing LLM context and memory management
- Building persistent knowledge bases for AI assistants
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