A local memory layer for AI coding tools that stores user preferences, lessons, and project context as local files, exposed via MCP so different AI tools can share the same understanding of you.
Provides AI agents with a governed, three-layer project memory (guide, code facts, and knowledge) through namespaced MCP tools for code search, context compilation, impact analysis, and proposal-driven documentation updates.
Aggregates your digital footprint (GitHub, blogs, resume) into a single AI-readable profile and exposes it via MCP tools so AI agents can query your context live.
Enables AI agents to securely access local development capabilities such as files, Git, processes, browser control, Windows automation, WSL, and observability through MCP on Windows and macOS.
Enables AI coding agents to maintain persistent, cross-session memory of codebase architecture, naming conventions, and decisions through MCP tools. Eliminates repetitive project re-explanation by automatically injecting stored context into every session with local-first SQLite storage and optional team sharing capabilities.