What is the Model Context Protocol (MCP)?

MCP is an open standard that enables LLMs to safely and reliably interact with external tools, data sources, and services through a standardized interface.

Does this skill support both Python and TypeScript?

Yes, it provides specific implementation guides, project structures, and best practices for both the TypeScript SDK and Python FastMCP.

How does mcp-builder help with Claude Code?

It allows you to build custom extensions (servers) that give Claude Code the ability to perform actions on your external APIs or local environment data.

What is the benefit of the evaluation phase?

The evaluation phase uses realistic question-answer pairs to ensure your tools are discoverable and that Claude can correctly solve complex tasks using your server.

Can I build remote servers with this guide?

Yes, the guide covers transport selection, including streamable HTTP for remote servers and stdio for local implementations.

MCP Server Builder

Name: MCP Server Builder
Author: MikeyB03

byMikeyB03

API Development

Guides the creation of high-quality Model Context Protocol (MCP) servers to extend LLM capabilities with external tools and services.

About

The mcp-builder skill provides a comprehensive framework for architecting, implementing, and testing Model Context Protocol (MCP) servers using TypeScript or Python. It helps developers navigate the complexities of tool design—balancing API coverage with specialized workflows—while providing structured guidance on transport mechanisms, error handling, and context management. By following its phase-based approach, developers can transition from basic API wrappers to sophisticated, discoverable integrations that enable AI agents to perform complex, real-world tasks with high reliability.

Key Features

Best practices for tool naming, discoverability, and input/output schema design
Curated reference library for protocol specifications and SDK documentation
0 GitHub stars
Step-by-step implementation workflows for TypeScript and Python FastMCP SDKs
Comprehensive evaluation framework for verifying AI tool-calling performance
Guidance on choosing between stdio and streamable HTTP transport mechanisms

Use Cases

Building a custom MCP server to connect private internal APIs to Claude Code
Developing specialized toolsets for cloud services using standardized design patterns
Refining existing MCP integrations to improve AI reliability through robust error handling

About

Key Features

Best practices for tool naming, discoverability, and input/output schema design
Curated reference library for protocol specifications and SDK documentation
0 GitHub stars
Step-by-step implementation workflows for TypeScript and Python FastMCP SDKs
Comprehensive evaluation framework for verifying AI tool-calling performance
Guidance on choosing between stdio and streamable HTTP transport mechanisms

Use Cases

Building a custom MCP server to connect private internal APIs to Claude Code
Developing specialized toolsets for cloud services using standardized design patterns
Refining existing MCP integrations to improve AI reliability through robust error handling