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 is easy to 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: You want to expose the GitHub API to an LLM agent. Follow the guide to design tools with proper naming, annotations, and pagination, then generate 10 evaluation questions and run the harness to measure agent accuracy. ## Quick Start Ask the assistant to help you build an MCP server for your chosen API, specifying whether you want TypeScript or Python.