What problem does it solve? Building MCP 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 - Phased Development Workflow: Walks through research and planning, implementation, code review, and evaluation creation for MCP servers. - Language-Specific Guides: Includes reference documentation for Python (FastMCP with Pydantic) and TypeScript (MCP SDK with Zod) implementations, plus MCP best practices. - Evaluation Harness: Ships Python scripts to connect to MCP servers over stdio, SSE, or HTTP and run XML-based QA evaluations against them using Claude. - 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 in TypeScript, then generate 10 complex evaluation questions and run the harness to measure how well an LLM can use your server. ## Quick Start Help me build an MCP server in TypeScript that wraps the GitHub API with tools for issues and pull requests.