An observational memory server that uses LLM agents to capture, compress, and recall project-specific decisions and context across AI coding sessions. It stores structured observations in SQLite to maintain long-term session continuity and architectural awareness.
A persistent, cross-session knowledge base for AI agents that indexes session history into a searchable SQLite database with full-text search, enabling recall of past sessions, stored knowledge, and summaries.
Persistent decision memory and contradiction detection for AI coding agents. Enforces architectural consistency across sessions — the agent cannot code until it loads prior decisions. Human resolves conflicts on a dashboard or in chat.
Persistent memory for AI coding agents, storing learned architecture decisions, patterns, and bug fixes in a local SQLite database with full-text search, enabling agents to recall information across sessions.
Provides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.
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.
