Does it include error handling best practices?

Yes, the skill provides detailed strategies for creating actionable, LLM-friendly error messages that help agents recover from failures and guide them toward correct usage.

Does this skill support both Python and Node.js?

Yes, it provides specific implementation guidance and best practices for both Python (via FastMCP) and Node/TypeScript (via the official MCP SDK).

What is an MCP server?

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

How do I test the MCP servers I build?

The skill includes a dedicated evaluation phase (Phase 4) that walks you through creating complex QA pairs and evaluation questions to verify your server's effectiveness in real-world scenarios.

How does this improve AI tool calling accuracy?

It emphasizes agent-centric design, which focuses on building high-signal workflow tools rather than just wrapping API endpoints, making it easier for AI agents to understand and use them.

MCP Server Builder

Name: MCP Server Builder
Author: nordeim

bynordeim

0•

API開発

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

This skill provides a comprehensive, four-phase framework for developing robust Model Context Protocol (MCP) servers in Python or TypeScript. It guides users through agent-centric design principles, implementation of tool-calling infrastructure, and the creation of rigorous evaluation harnesses, ensuring that resulting servers are optimized for context efficiency, reliability, and real-world AI agent workflows.

主な機能

01Agent-centric design principles for optimal tool usability and discoverability

020 GitHub stars

03Standardized evaluation frameworks for testing tool effectiveness through QA pairs

04Integrated strategies for input validation using Pydantic and Zod models

05Optimization techniques for context window constraints and token management

06Step-by-step implementation guides for Python (FastMCP) and TypeScript SDKs

ユースケース

01Integrating proprietary internal APIs with Claude for automated engineering workflows

02Developing standardized AI interfaces for complex database or cloud infrastructure management

03Building custom data retrieval tools for specialized SaaS platform integrations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nordeim/prompt-engineering mcp-builder

For use in Claude.ai and ChatGPT

Download Skill