How does it help with testing my implementation?

It features a dedicated evaluation phase that helps you create complex, real-world test cases in XML format to ensure your AI agent can reliably use the tools you've built.

Which programming languages are supported by this skill?

This skill provides specialized guidance and best practices for both TypeScript (via the official SDK) and Python (using the FastMCP framework).

What is an MCP server?

An MCP (Model Context Protocol) server is an open standard that enables AI models to connect to external data sources and tools through a unified, secure interface.

Does it provide guidance on API design?

Yes, it covers critical design aspects like tool naming for discoverability, handling pagination, and creating actionable error messages that help the AI self-correct.

Can I use this for local development?

Yes, the skill includes detailed instructions for setting up stdio transport, which is the standard for local servers and command-line tool integrations.

MCP Server Architect

Name: MCP Server Architect
Author: ZhanlinCui

byZhanlinCui

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API Development

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

About

MCP Server Architect provides a comprehensive framework for developing robust Model Context Protocol (MCP) servers in TypeScript or Python. It guides developers through the entire lifecycle of integration, from deep research and API planning to implementation using best practices for tool naming, context management, and error handling. This skill is essential for developers looking to extend Claude's capabilities by connecting it securely to custom data sources, internal tools, and third-party services using standardized communication protocols.

Key Features

Comprehensive guidance on transport mechanisms including stdio and streamable HTTP
17 GitHub stars
Best practices for actionable error messages and efficient context management
Optimized tool design with schema validation using Zod and Pydantic
Multi-language support for TypeScript SDK and Python FastMCP implementation
Integrated evaluation framework for testing AI tool effectiveness and reliability

Use Cases

Integrating proprietary internal company APIs into the Claude Code environment
Developing local system utilities using the stdio transport protocol for desktop automation
Building reusable connectors for SaaS platforms to automate complex workflows

About

Key Features

Comprehensive guidance on transport mechanisms including stdio and streamable HTTP
17 GitHub stars
Best practices for actionable error messages and efficient context management
Optimized tool design with schema validation using Zod and Pydantic
Multi-language support for TypeScript SDK and Python FastMCP implementation
Integrated evaluation framework for testing AI tool effectiveness and reliability

Use Cases

Integrating proprietary internal company APIs into the Claude Code environment
Developing local system utilities using the stdio transport protocol for desktop automation
Building reusable connectors for SaaS platforms to automate complex workflows