What is an MCP server?

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

What is the difference between API coverage and workflow tools?

API coverage provides raw access to endpoints for flexibility, while workflow tools are specialized, higher-level operations designed to help AI agents accomplish specific tasks more efficiently.

Does this skill support both Python and TypeScript?

Yes, it provides specific implementation patterns, project structures, and SDK guidance for both the TypeScript/Node.js and Python ecosystems.

How do I test my MCP server using this skill?

The skill guides you through using the MCP Inspector for manual testing and creating a structured XML evaluation file with 10 complex questions to verify AI performance.

What transport mechanisms are supported?

The guide covers both stdio transport (ideal for local development and CLI tools) and streamable HTTP transport (preferred for remote, scalable server deployments).

MCP Server Builder

Name: MCP Server Builder
Author: Daisuke134

byDaisuke134

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API Development

Guides the creation of high-quality Model Context Protocol (MCP) servers to integrate external APIs and services with LLMs.

About

The MCP Server Builder skill provides a comprehensive framework for developing robust Model Context Protocol (MCP) servers using TypeScript or Python. It streamlines the entire development lifecycle—from initial API research and tool naming strategy to implementing Zod/Pydantic schemas and error handling. By following this standardized guide, developers can build servers that enable AI agents to interact reliably with external data, complete with rigorous XML-based evaluation suites to ensure high-quality performance in real-world tasks.

Key Features

Comprehensive workflows for TypeScript (SDK) and Python (FastMCP) implementations.
Rigorous evaluation framework for testing tool effectiveness with realistic QA pairs.
Standardized schema design patterns using Zod and Pydantic for input validation.
3 GitHub stars
Guidance on implementing actionable error messages and pagination support.
Best practices for tool naming, discoverability, and context management.

Use Cases

Creating standardized API wrappers for third-party services like GitHub, Slack, or Jira.
Building custom MCP servers to connect internal databases or legacy systems to Claude.
Developing production-grade LLM tools with built-in evaluation and testing suites.

About

Key Features

Comprehensive workflows for TypeScript (SDK) and Python (FastMCP) implementations.
Rigorous evaluation framework for testing tool effectiveness with realistic QA pairs.
Standardized schema design patterns using Zod and Pydantic for input validation.
3 GitHub stars
Guidance on implementing actionable error messages and pagination support.
Best practices for tool naming, discoverability, and context management.

Use Cases

Creating standardized API wrappers for third-party services like GitHub, Slack, or Jira.
Building custom MCP servers to connect internal databases or legacy systems to Claude.
Developing production-grade LLM tools with built-in evaluation and testing suites.