An agent-agnostic memory layer that captures, reviews, and recalls facts from any coding agent, storing them locally as plain Markdown and speaking the Model Context Protocol.
A privacy-focused local memory server that provides long-term semantic storage and retrieval for AI agents using SQLite and ChromaDB. It enables LLMs to persist and query text, chat histories, and PDF documents across sessions through the Model Context Protocol.
Local-first memory and retrieval for private project knowledge. Enables indexing files, searching, and asking questions about project documents using local embeddings and LLM.
Gives AI agents durable project memory via the Model Context Protocol, allowing them to read tasks, record decisions, search context, and sync snapshots to the cloud.