MCP server that gives coding agents persistent, verified memory of codebase decisions, conventions, and skills, with evidence-based claims that are re-checked via git hooks and human-gated review. Enables memory search, propose/approve, chat harvesting, and critique across MCP-compatible tools.
MCP server that captures and recalls coding session memory (failures, decisions, diffs) for AI agents, enabling cross-agent continuity and preventing repeated mistakes.
Central MCP server for storing and querying lessons learned and project-specific implementation details, compatible with MCP-capable AI clients like Cursor, Claude Code, and Google Antigravity.
A local MCP server providing persistent memory for AI coding assistants by storing and searching architectural decisions, patterns, and solutions. It also includes tools for git automation and mapping codebase expertise based on project history.
A lightweight, local-first MCP server and CLI that helps developers and AI coding agents store and retrieve lessons learned during development, using SQLite and context-aware filtering.
MCP server that helps coding agents research and prepare GitHub contributions by gathering repository guidance, related work, code context, and validation evidence into a local SQLite corpus, without ever writing to GitHub.
