Memory Cache MCP Server

Efficiently reduces token consumption in Model Context Protocol interactions by automatically caching data such as file contents and computation results, enhancing performance and memory management across any MCP client and language model.

Provides persistent memory using a local knowledge graph with versioned entities, relations, and observations to enable context retention and dynamic information management across chats via the Model Context Protocol.

A Model Context Protocol server that leverages DuckDB to provide scalable, high-performance knowledge graph memory with efficient SQL-based querying, transaction support, and dynamic memory updates for enhanced context-aware interactions.

Provides persistent memory via a local knowledge graph for Model Context Protocol, enabling entity management, relationship mapping, observation tracking, and error lesson learning to enhance user context retention and adaptive interactions across chats.

Manages user-specific context for LLM interactions using in-memory storage and RESTful APIs, supporting the Model Context Protocol with efficient prompt history handling and TypeScript integration.