An MCP server for deterministic prompt optimization in Claude Code. Score prompts across 7 quality dimensions, auto-select from 11 Anthropic techniques, and return a structural scaffold.
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.
Deterministic context compression for MCP agents, reducing token usage via 11 tools for prompts, history, shell output, file deltas, and code navigation without ML or GPU.
Provides an MCP server that guides AI agents through a mandatory three-stage SOP to compress prompts and report token costs, reducing token usage by up to 40%.