Enables AI agents to store and retrieve design decisions as Markdown in git repositories, and check new proposals against historical decisions via MCP.
Record development decisions as structured JSON, embed them as vectors via Gemini, and search semantically over MCP. Works with Claude Code, Cursor, Windsurf, and any MCP client.
Automatically records AI conversation turns and code changes to local Markdown files to provide persistent context across chat sessions. It enables AI agents to search history through MCP tools and provides a web viewer for browsing past discussions.
Persistent memory for MCP-powered coding agents, allowing LLMs to remember preferences, project context, and decisions across sessions via Markdown files.
Enables AI agents to record and retrieve architectural decision records, check precedent before making decisions, and avoid repeating past mistakes or contradicting settled choices.
Enables AI coding agents to share a persistent local-first memory hub, storing and recalling architectural decisions and context across different tools via MCP, so users can switch assistants without losing context.