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 research, implementation, review, and evaluation. ## Core Features & Use Cases - End-to-End MCP Development Workflow: Guides you through research, planning, implementation, testing, and evaluation phases for MCP servers in Python (FastMCP) or TypeScript (MCP SDK). - Language-Specific Reference Guides: Includes detailed implementation patterns for Zod/Pydantic schemas, tool registration, pagination, error handling, and transport configuration (stdio vs streamable HTTP). - Evaluation Harness: Ships Python scripts to run automated evaluations that test whether LLMs can answer complex questions using only your MCP server's tools. - Use Case: You need to expose your company's internal API to an LLM assistant. Use this Skill to design well-named tools with proper annotations, implement the server in TypeScript, and generate 10 evaluation questions to verify quality. ## Quick Start Ask the agent to help you build an MCP server for your chosen API, specifying whether you want Python or TypeScript.