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.
An MCP server that provides controlled read/write tools for managing local-first research memory in an Obsidian vault, enabling AI agents to maintain project context across sessions.
A local-first MCP server that provides AI agents with safe codebase access through file discovery, hybrid lexical-semantic search, and project introspection. It features durable local memory and semantic indexing while keeping all data and processing entirely on your local machine.
MCP server for LeafMem, a layered memory engine that gives AI agents persistent, scoped memory with local retrieval and optional embedding rerank. It exposes tools for capturing turns, storing memories, and building recall context.