What problem does it solve? Building a Model Context Protocol server 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 - Four-Phase Development Workflow: Deep research and planning, implementation with FastMCP (Python) or the MCP TypeScript SDK, code review and testing with MCP Inspector, and evaluation creation. - Language-Specific References: Detailed guides for Python and Node/TypeScript covering project structure, Zod/Pydantic schemas, tool annotations, pagination, and error handling. - Evaluation Harness: Scripts to create 10-question XML evaluations and run them against your server via stdio, SSE, or streamable HTTP, producing accuracy reports with per-task feedback. - Use Case: You need to expose your company's internal API to Claude. Follow the workflow to design well-named tools with clear schemas, implement the server in TypeScript, then run the evaluation harness to verify an LLM can answer realistic questions using only your tools. ## Quick Start Ask the AI to help you build an MCP server for your chosen API, specifying whether you want Python with FastMCP or TypeScript with the MCP SDK.