Does this skill support both Python and TypeScript?

Yes, it provides detailed implementation guides for both the Python SDK (including FastMCP) and the Node/TypeScript MCP SDK.

What is an MCP server?

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

How does 'Agent-Centric Design' improve my tools?

It focuses on building tools around human-like workflows rather than just mirroring API endpoints, ensuring the AI can complete tasks more efficiently while staying within context window limits.

Can I use this to test my MCP tools?

Absolutely. The skill includes a dedicated phase for evaluation-driven development, helping you create 10+ realistic QA pairs to verify that your server handles complex, real-world requests correctly.

MCP Server Builder

Name: MCP Server Builder
Author: Jst-Well-Dan

byJst-Well-Dan

API Development

Streamlines the creation of high-quality Model Context Protocol (MCP) servers to connect AI agents with external tools and services.

About

This skill provides a comprehensive, step-by-step framework for architecting and implementing robust MCP servers using Python or TypeScript. It emphasizes agent-centric design principles, such as workflow-oriented tool creation and context window optimization, ensuring that resulting tools are highly effective for LLM interactions. From initial research and API planning to implementation and rigorous evaluation-driven development, this guide ensures your MCP integrations are production-ready, performant, and user-friendly.

Key Features

Comprehensive workflow for evaluation-driven development and testing
Strategic guidance on context window management and token optimization
Agent-centric design patterns for optimized AI interaction
0 GitHub stars
Dual-language support for Python (FastMCP) and Node/TypeScript SDKs
Standardized templates for tool documentation and input validation schemas

Use Cases

Creating automated evaluation suites to verify the reliability of tool-calling systems
Refactoring existing API wrappers into workflow-oriented tools for AI agents
Developing custom MCP servers to integrate proprietary business APIs with Claude

About

Key Features

Comprehensive workflow for evaluation-driven development and testing
Strategic guidance on context window management and token optimization
Agent-centric design patterns for optimized AI interaction
0 GitHub stars
Dual-language support for Python (FastMCP) and Node/TypeScript SDKs
Standardized templates for tool documentation and input validation schemas

Use Cases

Creating automated evaluation suites to verify the reliability of tool-calling systems
Refactoring existing API wrappers into workflow-oriented tools for AI agents
Developing custom MCP servers to integrate proprietary business APIs with Claude