How do I test the MCP servers I build?

The skill includes a dedicated evaluation phase where you create complex, multi-step test cases to verify that an LLM can successfully navigate your tools to solve real-world tasks.

What is an MCP server?

An MCP (Model Context Protocol) server is a specialized service that provides tools and resources, allowing LLMs like Claude to interact with external APIs, databases, and local files through a standardized protocol.

Does this skill support both Python and TypeScript?

Yes, it provides dedicated implementation guides for both Python (using FastMCP) and Node/TypeScript (using the official MCP SDK), including environment setup and best practices for each.

What is agent-centric design?

Agent-centric design is a methodology that focuses on building tools specifically for LLM consumption, prioritizing concise, high-signal data and actionable error messages over raw API output.

MCP Server Builder

Name: MCP Server Builder
Author: Primadetaautomation

byPrimadetaautomation

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API 开发

Streamlines the creation of high-quality Model Context Protocol (MCP) servers using agent-centric design patterns and multi-language SDKs.

关于

The MCP Server Builder skill provides a comprehensive framework for developing robust Model Context Protocol (MCP) servers that allow Claude and other LLMs to interact seamlessly with external services. It guides developers through the entire lifecycle of server creation—from agent-centric design and protocol research to implementation in Python or TypeScript and rigorous evaluation. By focusing on workflow-oriented tool design and context optimization, this skill ensures that your integrations are not just functional, but highly effective for AI agents operating within constrained context windows.

主要功能

Step-by-step workflows for Python (FastMCP) and Node/TypeScript SDKs
Comprehensive evaluation framework for testing tool-calling reliability
Automated documentation fetching for the latest MCP protocol specifications
Best practices for input validation, error handling, and response formatting
Agent-centric design principles focused on high-signal tool outputs
4 GitHub stars

使用场景

Building custom integrations to connect internal company APIs with Claude Code
Optimizing existing API wrappers to improve AI agent performance and context usage
Developing standardized evaluation suites to verify the accuracy of complex tool workflows

关于

主要功能

Step-by-step workflows for Python (FastMCP) and Node/TypeScript SDKs
Comprehensive evaluation framework for testing tool-calling reliability
Automated documentation fetching for the latest MCP protocol specifications
Best practices for input validation, error handling, and response formatting
Agent-centric design principles focused on high-signal tool outputs
4 GitHub stars

使用场景

Building custom integrations to connect internal company APIs with Claude Code
Optimizing existing API wrappers to improve AI agent performance and context usage
Developing standardized evaluation suites to verify the accuracy of complex tool workflows