How does this skill improve AI agent tool usage?

It teaches agent-centric design, focusing on building high-impact workflows rather than simple API wrappers, and optimizing data returns for limited context windows.

What languages does the mcp-builder skill support?

It provides detailed implementation guides and best practices for both Python (using FastMCP) and Node/TypeScript environments.

Does it include testing and evaluation features?

Yes, it includes a specific phase for creating evaluation harnesses using XML-based QA pairs to ensure your MCP server handles complex, real-world tasks reliably.

Can I use this to connect Claude to my own private APIs?

Absolutely. The skill is designed to help you build the bridge between Claude and any external or internal service using the Model Context Protocol.

MCP Server Builder

Name: MCP Server Builder
Author: kivilaid

bykivilaid

•

API 开发

Guides the creation of high-quality Model Context Protocol (MCP) servers for both Python and TypeScript environments.

关于

The mcp-builder skill provides a structured, professional framework for developing Model Context Protocol (MCP) servers that enable AI agents to interact seamlessly with external services. It emphasizes agent-centric design principles, ensuring tools are optimized for limited context windows and provide actionable feedback. By walking developers through deep research, robust implementation with Pydantic or Zod schemas, and the creation of comprehensive evaluation harnesses, this skill ensures that your MCP servers are production-grade, reliable, and highly effective for LLM interactions.

主要功能

Automated retrieval of the latest MCP protocol and SDK documentation via WebFetch.
Agent-centric design principles to optimize tool performance for context-constrained LLMs.
Step-by-step workflow for Python (FastMCP) and TypeScript MCP implementation.
Comprehensive guidance for input validation and schema design using Pydantic and Zod.
Built-in evaluation framework for creating verifiable, complex testing scenarios.
6 GitHub stars

使用场景

Building custom toolkits that allow Claude to interact securely with internal company APIs.
Wrapping complex SaaS web services into a standardized protocol for AI agent usage.
Optimizing existing API integrations to be more 'agent-friendly' through better error handling and task subdivision.

关于

主要功能

Automated retrieval of the latest MCP protocol and SDK documentation via WebFetch.
Agent-centric design principles to optimize tool performance for context-constrained LLMs.
Step-by-step workflow for Python (FastMCP) and TypeScript MCP implementation.
Comprehensive guidance for input validation and schema design using Pydantic and Zod.
Built-in evaluation framework for creating verifiable, complex testing scenarios.
6 GitHub stars

使用场景

Building custom toolkits that allow Claude to interact securely with internal company APIs.
Wrapping complex SaaS web services into a standardized protocol for AI agent usage.
Optimizing existing API integrations to be more 'agent-friendly' through better error handling and task subdivision.