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 testing, which developers often get wrong without structured guidance. ## Core Features & Use Cases - Four-Phase Development Workflow: Covers research and planning, implementation, review and testing, and evaluation creation for MCP servers. - Language-Specific Guides: Provides reference documentation for TypeScript (MCP SDK with Zod) and Python (FastMCP with Pydantic) implementations. - Evaluation Harness: Includes Python scripts to run XML-based QA evaluations against MCP servers over stdio, SSE, or streamable HTTP transports. - Use Case: A developer integrating the GitHub API into an LLM agent uses this Skill to scaffold a well-named, paginated, annotated MCP server and then verify it with 10 read-only evaluation questions. ## Quick Start Ask the AI to help you build an MCP server for your chosen API, specifying whether you want TypeScript or Python.