How do I test my MCP server?

You can use the official MCP Inspector to verify tool functionality and transport mechanisms like stdio or streamable HTTP.

What is an MCP server?

An MCP (Model Context Protocol) server is a specialized backend that enables LLMs to interact with external data and services through defined tools and resources.

Does this help with deployment?

Yes, it includes guidance for local development and one-click cloud deployment specifically optimized for MCP servers.

Why are evaluations included in the process?

Evaluations ensure that an LLM can effectively use the tools you have built to solve complex, real-world tasks accurately and consistently.

Which languages are supported by this skill?

The skill provides detailed implementation patterns for both Python (using FastMCP 2.0) and Node.js/TypeScript.

MCP Server Builder

Name: MCP Server Builder
Author: timequity

bytimequity

API Development

Builds high-quality Model Context Protocol (MCP) servers to connect LLMs with external APIs and services through well-designed tools.

About

This skill provides a comprehensive framework for developing robust MCP servers using Python (FastMCP) or TypeScript. It guides developers through the entire lifecycle—from deep research and API planning to implementation, testing, and creating evaluation datasets—ensuring tools are discoverable, well-documented, and optimized for agentic workflows. By following these standardized patterns, you can create performant integrations that allow Claude and other models to interact seamlessly with external data sources and complex software ecosystems.

Key Features

Best practices for tool naming, discoverability, and context management
Support for Python (FastMCP 2.0) and TypeScript SDKs
0 GitHub stars
Standardized patterns for error handling, pagination, and data schemas
Automated evaluation generation for testing LLM tool-calling accuracy
Integrated testing workflows using the MCP Inspector

Use Cases

Creating specialized workflow tools for SaaS platforms like GitHub or Slack
Building custom MCP servers to integrate internal company APIs with Claude
Developing high-performance remote MCP servers using streamable HTTP transport

About

Key Features

Best practices for tool naming, discoverability, and context management
Support for Python (FastMCP 2.0) and TypeScript SDKs
0 GitHub stars
Standardized patterns for error handling, pagination, and data schemas
Automated evaluation generation for testing LLM tool-calling accuracy
Integrated testing workflows using the MCP Inspector

Use Cases

Creating specialized workflow tools for SaaS platforms like GitHub or Slack
Building custom MCP servers to integrate internal company APIs with Claude
Developing high-performance remote MCP servers using streamable HTTP transport