Automatically extracts architectural decisions, patterns, and insights from Git commits to build a local, structured project memory. It exposes this living context to AI tools via MCP, allowing them to understand the historical reasoning and evolution behind your codebase.
Local-first codebase context engine that parses code into a ranked dependency graph and serves it to AI tools via MCP for deep structural understanding.
Enables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.
Persistent project memory and task management for AI coding agents through MCP. Lets Claude Code, Cursor, Codex and other MCP clients save decisions and bug fixes, search relevant context, and reuse it across sessions.