How does this help with LLM context windows?

The skill includes specific guidance on designing tools for limited context, such as returning high-signal information, using concise response formats, and implementing truncation strategies.

Can I test my MCP server using this skill?

Yes, the skill includes a dedicated phase for creating evaluations and XML-based QA pairs to verify that your server functions correctly and provides accurate data in real-world scenarios.

What is an MCP server?

An MCP (Model Context Protocol) server is a specialized backend that provides tools and resources, allowing LLMs like Claude to interact safely with external APIs, databases, and local services.

Which programming languages are supported by this skill?

This skill provides specialized implementation guides and best practices for both Python (using FastMCP and the Python SDK) and Node.js/TypeScript (using the TypeScript SDK).

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

It is the practice of building tools around high-impact workflows rather than just wrapping API endpoints, ensuring tools are intuitive for AI agents to discover and use effectively.

MCP Server Builder

Name: MCP Server Builder
Author: Ven0m0

byVen0m0

API開発

Generates production-grade Model Context Protocol (MCP) servers in Python and TypeScript to connect LLMs with external APIs and services.

概要

The MCP Server Builder skill provides a comprehensive framework for developing high-quality Model Context Protocol servers. It guides developers through the entire lifecycle—from agent-centric design principles and API research to implementing schemas with Pydantic or Zod and creating robust evaluation harnesses. Whether using Python's FastMCP or the TypeScript SDK, this skill ensures your tools are optimized for AI context limits, handle errors gracefully, and deliver high-signal data for seamless agentic workflows.

主な機能

Multi-language support for Python (FastMCP) and TypeScript (MCP SDK) implementations
0 GitHub stars
Agent-centric design patterns to optimize for LLM context windows and token usage
Automated schema generation using Pydantic (Python) and Zod (TypeScript)
Integrated evaluation framework to verify tool performance with realistic QA scenarios
Standardized workflow for API integration, research, and documentation fetching

ユースケース

Optimizing existing tool schemas to improve agent reliability and error handling
Developing public MCP servers for third-party SaaS platforms and developer tools
Building custom bridges between internal corporate APIs and Claude Code

概要

主な機能

Multi-language support for Python (FastMCP) and TypeScript (MCP SDK) implementations
0 GitHub stars
Agent-centric design patterns to optimize for LLM context windows and token usage
Automated schema generation using Pydantic (Python) and Zod (TypeScript)
Integrated evaluation framework to verify tool performance with realistic QA scenarios
Standardized workflow for API integration, research, and documentation fetching

ユースケース

Optimizing existing tool schemas to improve agent reliability and error handling
Developing public MCP servers for third-party SaaS platforms and developer tools
Building custom bridges between internal corporate APIs and Claude Code