What problem does it solve? Building Model Context Protocol servers that LLMs can actually use effectively requires careful tool design, schema validation, transport selection, and evaluation—this Skill provides a structured four-phase workflow covering all of it. ## Core Features & Use Cases - End-to-End MCP Development Workflow: Walks through research, implementation, review, and evaluation phases for building MCP servers in Python (FastMCP) or TypeScript (MCP SDK). - Language-Specific Reference Guides: Includes detailed implementation guides covering Zod/Pydantic schemas, tool registration, pagination, error handling, and transport configuration (stdio vs streamable HTTP). - Evaluation Harness: Ships Python scripts to create XML-based evaluation question sets and run automated LLM-based tests against your MCP server via stdio, SSE, or HTTP. - Use Case: You want to expose your company's internal API to Claude. Use this Skill to scaffold a TypeScript MCP server with well-named tools, then generate 10 evaluation questions and run the harness to verify LLMs can answer realistic queries. ## Quick Start Ask the agent to help you build an MCP server for your chosen API, specifying whether you want Python or TypeScript.