A self-learning MCP server for Claude Code that captures user corrections and tool failures, distills them into skill drafts, and activates them only after human approval.
An MCP server that enables Claude to learn from user corrections by recording them as persistent rules in CLAUDE.md files. It manages project-specific or global guidelines to ensure the assistant avoids repeating the same mistakes in future sessions.
Enables AI agents to learn from their work by recording tasks, extracting patterns, detecting mistakes, and proactively surfacing insights, all using the agent's own model through a cooperative intelligence pattern.
Enables context capture and reinforcement learning by recording successful work patterns and creating reasoning chains for cross-conversation continuity. Automatically captures positive feedback through Claude Code hooks to build reusable success patterns.
A self-learning AI standards system that automatically detects patterns from user corrections and updates AI configuration files. Learns from repeated corrections (like 'use uv not pip') and automatically generates CLAUDE.md and other AI assistant configuration files.