Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.

Provides AI coding agents with an embedded knowledge graph and architecture governance tools, enabling blast radius analysis, compliance checks, and smart context extraction from codebases.

Persistent memory system for Claude Code via Markdown. Setup with /init-project, resume with /catchup, wrap with /wrapup. Includes coding standards, MCP servers, and modular skills. Solves context loss after /clear.

A long-term memory system built for AI Agents. Agent wakes up already knowing who he is, not querying "who am I?" every session. Every turn calling back accurate memory context. Achieving accurate memory hits while also preventing memory from expanding at scale. No compression, no forgetting.

A Model Context Protocol (MCP) server that retrieves information from Wikipedia to provide context to LLMs.

InfoLang semantic memory MCP — investigate, memorize, and recall compressed agent context.