How do I test the quality of my MCP server?

The skill guides you through using the MCP Inspector for functional testing and provides a framework for creating 10-question evaluation sets to verify LLM performance.

Which programming languages does this skill support?

This skill provides detailed implementation guides and best practices for both TypeScript (using the official SDK) and Python (using the FastMCP framework).

Does this skill help with MCP error handling?

Yes, it provides specific patterns for creating actionable error messages that guide the AI toward a solution rather than just reporting a failure.

What is an MCP server?

A Model Context Protocol (MCP) server is a standardized bridge that allows Large Language Models (LLMs) to securely interact with external data sources, APIs, and local tools.

What is the difference between workflow tools and API coverage?

API coverage provides the LLM with raw building blocks, while workflow tools combine multiple steps into one. This skill recommends prioritizing comprehensive API coverage for maximum flexibility.

MCP Server Builder

Name: MCP Server Builder
Author: macnversion

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API 개발

Guides developers through the end-to-end process of building, testing, and evaluating high-quality Model Context Protocol (MCP) servers.

소개

The MCP Server Builder skill provides a comprehensive framework for creating robust Model Context Protocol (MCP) servers that enable LLMs to interact seamlessly with external services. It streamlines the entire development lifecycle, offering deep research strategies, architectural planning, and implementation patterns for both TypeScript and Python. By emphasizing best practices in tool naming, context management, and structured error handling, this skill helps developers build production-grade integrations that significantly enhance the capabilities of AI agents.

주요 기능

Comprehensive workflow for MCP server planning and implementation
Standardized patterns for tool discovery and context management
Best practices for actionable error messages and API coverage
Dual-language support for TypeScript (SDK) and Python (FastMCP)
Built-in guidance for creating verifiable evaluation suites
0 GitHub stars

사용 사례

Standardizing MCP development workflows across engineering teams
Building custom integrations to connect internal APIs with AI agents
Developing reusable toolsets for third-party service interactions

소개

주요 기능

Comprehensive workflow for MCP server planning and implementation
Standardized patterns for tool discovery and context management
Best practices for actionable error messages and API coverage
Dual-language support for TypeScript (SDK) and Python (FastMCP)
Built-in guidance for creating verifiable evaluation suites
0 GitHub stars

사용 사례

Standardizing MCP development workflows across engineering teams
Building custom integrations to connect internal APIs with AI agents
Developing reusable toolsets for third-party service interactions