How should I safely test a new MCP server?

The guide recommends using an evaluation harness or running the server in a separate process like tmux to prevent the long-running stdio process from hanging your main development environment.

How do I verify the quality of my MCP implementation?

The skill includes a systematic review process and an evaluation guide to create 10 complex, realistic questions that verify your server's effectiveness through string comparison.

What is 'Agent-Centric Design' in the context of MCP?

It is a design philosophy that focuses on building tools for workflows rather than just endpoints, optimizing for limited context windows and providing actionable error messages for the AI.

What is the primary purpose of this MCP development skill?

It provides a standardized methodology for building Model Context Protocol servers that allow LLMs to interact reliably with external services through well-designed tools.

Does it support both Python and TypeScript?

Yes, the skill includes specific implementation guides and quality checklists for both the Python (FastMCP) and Node/TypeScript SDKs.

MCP Server Builder

Name: MCP Server Builder
Author: Justdvp

byJustdvp

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Desarrollo de API

Guides the creation of high-quality Model Context Protocol (MCP) servers to connect Claude with external APIs and services.

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This skill provides a comprehensive, four-phase framework for developing robust Model Context Protocol (MCP) servers in Python or TypeScript. It bridges the gap between raw API endpoints and AI-ready tools by emphasizing agent-centric design principles, such as context window optimization and actionable error messaging. Whether you are building with FastMCP or the TypeScript SDK, this guide ensures your integration follows industry best practices for implementation, security, and systematic evaluation using realistic testing scenarios.

Características Principales

Step-by-step workflow from deep research to deployment
Comprehensive evaluation framework for testing tool effectiveness
Robust error handling and input validation patterns
Agent-centric design principles for optimized AI tool usage
5 GitHub stars
Language-specific implementation guides for Python and Node.js

Casos de Uso

Building custom MCP servers to integrate proprietary internal APIs with Claude
Establishing a standardized development and testing pipeline for new LLM tools
Refactoring existing API wrappers to be more 'agent-friendly' and context-efficient

Acerca de

Características Principales

Step-by-step workflow from deep research to deployment
Comprehensive evaluation framework for testing tool effectiveness
Robust error handling and input validation patterns
Agent-centric design principles for optimized AI tool usage
5 GitHub stars
Language-specific implementation guides for Python and Node.js

Casos de Uso

Building custom MCP servers to integrate proprietary internal APIs with Claude
Establishing a standardized development and testing pipeline for new LLM tools
Refactoring existing API wrappers to be more 'agent-friendly' and context-efficient