What schema libraries are recommended?

The skill recommends using Zod for TypeScript projects and Pydantic for Python projects to ensure robust input/output validation and clear tool descriptions.

How does it help with tool testing?

It includes a structured evaluation phase that helps you create XML-based test cases to verify the LLM can correctly call your tools to solve complex problems.

Does it support both Python and TypeScript?

Yes, it provides dedicated implementation patterns, project structures, and best practices for both the TypeScript SDK and the Python FastMCP framework.

Can I build both local and remote servers?

Absolutely. The skill covers using stdio for local implementations and streamable HTTP for remote, scalable server architectures.

What is the MCP Server Builder skill?

It is a specialized guide and framework for creating servers that follow the Model Context Protocol, allowing AI models like Claude to interact with external applications and data.

MCP Server Builder

Name: MCP Server Builder
Author: partme-ai

bypartme-ai

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API Development

Builds high-quality Model Context Protocol (MCP) servers to seamlessly integrate LLMs with external APIs and services.

About

The mcp-builder skill provides a comprehensive framework for developing, testing, and evaluating MCP servers using either TypeScript or Python. It guides developers through the entire lifecycle of server creation—from initial API research and transport selection to implementing robust tools with strict schema validation. By following these best practices, developers can create reliable interfaces that allow AI models to perform complex, real-world tasks through well-designed tool sets and automated evaluation suites.

Key Features

Automated evaluation generation for testing tool reliability
Comprehensive integration with official MCP protocol documentation
Standardized MCP server architecture for TypeScript and Python
Best practices for actionable error handling and context management
37 GitHub stars
Advanced tool design guidance with Zod and Pydantic validation

Use Cases

Creating custom toolsets for Claude to interact with internal enterprise APIs
Developing production-ready remote integrations using streamable HTTP
Building local MCP servers to extend LLM capabilities with system-level access

About

Key Features

Automated evaluation generation for testing tool reliability
Comprehensive integration with official MCP protocol documentation
Standardized MCP server architecture for TypeScript and Python
Best practices for actionable error handling and context management
37 GitHub stars
Advanced tool design guidance with Zod and Pydantic validation

Use Cases

Creating custom toolsets for Claude to interact with internal enterprise APIs
Developing production-ready remote integrations using streamable HTTP
Building local MCP servers to extend LLM capabilities with system-level access