An MCP server that reduces token usage by lazily loading skills and tools only when needed, and routing repetitive subtasks to ML backends instead of the LLM.
A production-ready MCP server that equips AI agents with dynamic, persistent, and executable skills. It enables secure script execution and progressive disclosure to reduce context window usage.
An MCP server that provides intelligent discovery, search, and on-demand loading of Claude Code skills and agents, reducing token usage by lazy loading.
A universal MCP server that enables any MCP-compatible agent to use Anthropic's Claude Agent Skills with progressive disclosure, reducing context overhead while maximizing capability.
Universal MCP server for executing TypeScript and Python code with progressive disclosure, reducing token usage by 98% by enabling on-demand access to all other MCP tools through code execution rather than loading tool definitions directly.