Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.
Provides any AI CLI tool with long-term memory using a three-tier architecture (sensory, short-term, long-term) for cross-session persistence, fully local and private.
A local-first memory layer for coding agents to persist and retrieve project decisions, architecture context, and rules across multiple development sessions. It utilizes a three-tier memory model and hybrid retrieval to provide agents with durable, searchable context and a WebUI for human review.
An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.
An AI memory system that creates isolated, persistent memory banks for each codebase, solving the context-switching problem by keeping project knowledge separate and accessible across sessions.
Provides AI agents with persistent, searchable memory that survives across conversations using semantic search, temporal versioning, and smart organization. Enables long-term context retention and cross-session continuity for AI assistants.