What problem does it solve? AI agents waste thousands of tokens loading full tool schemas for MCP servers and APIs, and integrating each new API normally requires writing custom client code. This Skill turns any MCP server, OpenAPI spec, or GraphQL endpoint into a CLI at runtime, cutting tool schema token costs by 96-99%. ## Core Features & Use Cases - Runtime API-to-CLI Conversion: Introspect MCP (HTTP/SSE and stdio), OpenAPI, and GraphQL sources and expose their operations as subcommands with no codegen step. - Baked Named Configurations: Save connection settings, auth, and tool filters once, then invoke them with a short @name prefix or install them as standalone commands. - Token-Efficient Output: Use compact listings, usage-based tool ranking, and TOON encoding to minimize tokens sent to AI agents. - Use Case: Connect an AI agent to a GitHub MCP server by baking the configuration once, then run commands like mcp2cli @github search-repositories --query "rust" while only spending ~20 tokens on tool discovery instead of ~1,400. ## Quick Start Ask the agent to list the available tools from an MCP server or OpenAPI spec by running mcp2cli with the server URL or spec path and the --list flag.