How do I test the MCP servers I build?

The skill includes a dedicated evaluation phase (Phase 4) that guides you through creating QA pairs and using evaluation harnesses to verify tool reliability.

What is an MCP server?

A Model Context Protocol (MCP) server is a standardized interface that allows Large Language Models to safely and effectively interact with external data, APIs, and local services.

Does this skill support both Python and TypeScript?

Yes, it provides specific implementation guides for the Python SDK (using FastMCP) and the Node/TypeScript SDK.

What are agent-centric design principles?

It is a design philosophy that focuses on building tools for LLM workflows rather than simple API wrappers, optimizing for limited context and actionable error messages.

MCP Server Builder

Name: MCP Server Builder
Author: Activer007

byActiver007

API 开发

Guides developers through building high-quality Model Context Protocol (MCP) servers to integrate external APIs with LLMs.

关于

This skill provides a comprehensive, agent-centric framework for developing robust MCP servers in Python and TypeScript. It streamlines the entire development lifecycle—from deep API research and workflow-oriented tool design to implementation best practices and evaluation-driven development. By following this guide, developers can create high-signal integrations that allow Claude and other LLMs to interact effectively with external services through well-designed, context-efficient tools.

主要功能

Step-by-step workflow for Python (FastMCP) and Node/TypeScript SDKs
Automated evaluation generation to verify tool performance and stability
Agent-centric tool design principles focused on workflows over endpoints
Reference documentation for MCP protocol and framework best practices
Implementation patterns for robust input validation and error handling
0 GitHub stars

使用场景

Building enterprise-grade MCP servers for secure internal service access
Optimizing existing toolsets for better context window efficiency
Creating custom API integrations for Claude Code and LLM agents

关于

主要功能

Step-by-step workflow for Python (FastMCP) and Node/TypeScript SDKs
Automated evaluation generation to verify tool performance and stability
Agent-centric tool design principles focused on workflows over endpoints
Reference documentation for MCP protocol and framework best practices
Implementation patterns for robust input validation and error handling
0 GitHub stars

使用场景

Building enterprise-grade MCP servers for secure internal service access
Optimizing existing toolsets for better context window efficiency
Creating custom API integrations for Claude Code and LLM agents