Token-efficient MCP reimplementation with progressive tool discovery, result handling, and compact wire encoding, reducing token usage by up to 89% on tool definitions.
Agent-optimized MCP server that replaces built-in file, search, exec, and git tools with compact, structured JSON equivalents. Benchmarked 20–45% token savings for AI coding agents.
An MCP server that lets agents and humans monitor and control long-running processes, reducing copy-pasting between AI tools and enabling multiple agents to interact with the same process outputs.
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.