A persistent, local memory layer for AI coding agents that remembers decisions, bugs, and rules across sessions with three core MCP verbs (recall, remember, search).
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.
Provides AI coding assistants with persistent project memory to retain architectural decisions, code patterns, and domain knowledge across sessions. It stores data locally in a SQLite database, allowing agents to remember, recall, and manage project-specific context using full-text search.
Provides persistent, searchable memory and knowledge capture for AI-assisted development, enabling agents to retain decisions, bugs, and patterns across sessions and projects.
Provides persistent, local-first memory with knowledge graph and hybrid search for AI coding agents, reducing token usage by storing decisions, patterns, and codebase context.
Provides long-term memory for AI coding agents, enabling them to remember, search, and organize information across sessions and platforms like Claude Code, ChatGPT, and Cursor.