How do I verify that my MCP server works correctly?

The skill includes an Evaluation Guide that teaches you how to create XML-based evaluation pairs to test if an LLM can successfully navigate your tools to solve complex, real-world tasks.

Does this skill support both Python and TypeScript?

Yes, it provides detailed implementation patterns and documentation for both the TypeScript SDK and the Python FastMCP framework.

What is the difference between API coverage and workflow tools?

API coverage provides granular access to endpoints for flexibility, while workflow tools combine multiple operations into a single high-level task for agent efficiency.

What is an MCP server?

An MCP (Model Context Protocol) server is a standardized interface that allows Large Language Models like Claude to interact with external data sources, tools, and services through a common protocol.

Can I build both local and remote MCP servers?

Yes, the guide covers transport mechanisms for both local development (stdio) and remote, scalable production environments (streamable HTTP).

MCP Server Development Guide

Name: MCP Server Development Guide
Author: theflysurfer

bytheflysurfer

API開発

Architects high-quality Model Context Protocol (MCP) servers to seamlessly integrate external APIs and services with LLMs.

概要

This skill provides a comprehensive, step-by-step framework for building robust Model Context Protocol (MCP) servers using TypeScript or Python. It guides developers through the entire lifecycle of MCP creation—from strategic API research and tool naming conventions to implementing advanced patterns like pagination, structured data outputs, and actionable error handling. By following this standardized guide, you can ensure your MCP servers are highly discoverable for AI agents, performance-optimized, and verified through rigorous evaluation suites, bridging the gap between Claude and your custom data or services.

主な機能

Best practices for input validation using Zod/Pydantic and robust error reporting.
Support for multiple transport layers including stdio and streamable HTTP.
0 GitHub stars
Strategic guidance on tool naming, discoverability, and context management.
Automated evaluation generation for testing tool effectiveness and accuracy.
Comprehensive implementation patterns for TypeScript SDK and Python FastMCP.

ユースケース

Building custom bridges between proprietary enterprise APIs and Claude Code.
Modernizing legacy internal tools into structured MCP formats for AI agent accessibility.
Developing complex multi-tool workflows that require reliable pagination and structured data.

概要

主な機能

Best practices for input validation using Zod/Pydantic and robust error reporting.
Support for multiple transport layers including stdio and streamable HTTP.
0 GitHub stars
Strategic guidance on tool naming, discoverability, and context management.
Automated evaluation generation for testing tool effectiveness and accuracy.
Comprehensive implementation patterns for TypeScript SDK and Python FastMCP.

ユースケース

Building custom bridges between proprietary enterprise APIs and Claude Code.
Modernizing legacy internal tools into structured MCP formats for AI agent accessibility.
Developing complex multi-tool workflows that require reliable pagination and structured data.