What problem does it solve? Building MCP (Model Context Protocol) servers that LLMs can actually use effectively requires careful tool design, schema validation, transport selection, and testing—this Skill provides a structured four-phase workflow covering research, implementation, review, and evaluation. ## Core Features & Use Cases - Guided Development Workflow: Walks through deep research of the MCP specification, framework documentation, and API planning before writing code. - Language-Specific References: Includes implementation guides for Python (FastMCP) and Node/TypeScript (MCP SDK) with Zod/Pydantic validation patterns, naming conventions, and quality checklists. - Evaluation Harness: Ships Python scripts to create XML-based evaluation question sets and run automated tests against your MCP server via stdio, SSE, or HTTP transports. - Use Case: You need to expose your company's internal API to Claude. Use this Skill to design well-named tools with proper annotations, implement the server in TypeScript, then generate 10 complex evaluation questions to verify LLMs can actually accomplish real tasks with it. ## Quick Start Ask the AI to help you build an MCP server for your chosen API, specifying whether you want to use Python with FastMCP or TypeScript with the MCP SDK.