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.
Provides AI agents with a local, private Markdown-based memory vault and SQLite search. Enables agents to search, read, list, and traverse linked knowledge pages via MCP with zero external runtime dependencies.
A local-first shared memory layer for MCP-aware agents like Claude, Codex, and Hermes, enabling persistent memory across chats and clients via Markdown files and SQLite FTS.
A local markdown memory and cross-agent context engine for AI coding assistants. It provides an MCP server with tools to search, add, retrieve, and distill persistent memory across tools like Claude Code, Cursor, and Zed.
Provides a file-first personal memory layer for AI agents, enabling them to store and retrieve memories as markdown files with an SQLite index. The MCP server offers read-only search by default, with optional write tools for manual memory addition and conflict resolution.