What problem does it solve? Building an MCP (Model Context Protocol) server 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 TypeScript (MCP SDK) or Python (FastMCP). - 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 need to expose your company's internal API to LLM agents. Use this Skill to design well-named tools with proper annotations, implement the server, and validate quality with 10 complex read-only evaluation questions. ## Quick Start Help me build an MCP server that integrates the GitHub API with tools for issues, pull requests, and repositories.