A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.
A Model Context Protocol server providing pre-curated canonical memory, prose/code provenance checking, and benchmark metrics to improve accuracy and reduce costs across AI tools.
Model Context Protocol server for conversation compression that reduces token consumption using deterministic, embedding-free compression with mode-aware strategies.
A Model Context Protocol server that provides persistent memory and conversation continuity for Claude Desktop and Claude Code, allowing users to save and restore project context when threads hit token limits.
A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.