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 CLI that mines git history for file-level co-change patterns and builds a queryable knowledge graph for AI coding agents, exposed via an MCP server.
Provides MCP tools that give AI agents persistent, append-only memory in a git repository, letting them record observations, decisions, and corrections while retrieving context briefs, current facts, conflicts, and traceable event history without a vector database.
An MCP server that gives AI agents git repository access: status, log, diff, branch, commit, push, pull, tag, stash, remotes — 24 tools, zero dependencies, pure Python stdlib (subprocess).