An MCP server suite that optimizes prompt context by reducing tokens up to 98.8%, acting as persistent long-term memory and codebase scanner to save API costs.
An MCP server that reduces Manus AI credit usage by up to 75% through intelligent prompt compression, smart model routing, and intent classification. It provides tools to analyze and optimize prompts for maximum efficiency without sacrificing quality.
An MCP server that helps AI agents reduce token usage by converting data to TOON format and stripping comments and unnecessary whitespace from code files.
MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.