Provides persistent, inspectable memory storage for AI agents using SQLite. Agents can store, recall, and search memories across sessions via three MCP tools.
Enables AI-assisted diary management through natural language, allowing you to create, read, update, delete, and search diary entries stored locally in SQLite.
Enables AI agents to track, search, and retrieve their progress across projects with persistent memory using SQLite storage and LLM-powered summarization. Supports logging completed work, searching previous entries, and retrieving context for multi-step or multi-agent workflows.
SQLite-backed memory storage for MCP agents with optional semantic search via OpenAI embeddings, enabling agents to remember, recall, and manage contextual information across sessions.
Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.