Memorious
0
Provides a persistent key-value memory store with vector-similarity lookup using ChromaDB.
About
Memorious offers a robust, minimal Model Context Protocol (MCP) server designed to equip AI models with a persistent memory store. It leverages ChromaDB as its backend to facilitate efficient key-value storage alongside powerful vector-similarity lookup capabilities. This allows AI agents to store and retrieve information semantically, enhancing their ability to recall relevant context based on learned experiences, making it an essential component for building more intelligent and context-aware applications.
Key Features
- FastMCP-based stdio server exposing 'store', 'recall', and 'forget' tools.
- ChromaDB backend for persistent data storage on disk using Chroma's PersistentClient.
- Vector-similarity lookup for semantic information retrieval.
- Standard Python package layout for easy installation and distribution.
- Configurable memory persistence directory.
- 0 GitHub stars
Use Cases
- Equipping AI models with persistent memory for contextual conversations.
- Storing and retrieving information based on semantic similarity rather than exact matches.
- Managing an AI agent's knowledge base, allowing it to remember and forget specific data.