Can I build both local and remote MCP servers?

Yes, the guide covers multiple transport mechanisms, including stdio for local implementations and streamable HTTP for remote, scalable deployments.

Does this skill support both Python and TypeScript?

Yes, it provides comprehensive implementation guides, project structures, and best practices for both the Python (FastMCP) and TypeScript SDKs.

What is an MCP server?

An MCP (Model Context Protocol) server is a standardized interface that allows AI models to interact securely and reliably with external data sources, services, and tools.

How does this help with tool discoverability?

The skill enforces standardized naming conventions and descriptive metadata, ensuring that LLMs can easily find and correctly utilize the right tools for a given task.

What is the purpose of the evaluation phase?

Evaluations use verifiable Q&A pairs to test whether an LLM can effectively navigate your MCP server's tools to solve complex, realistic problems.

MCP Server Builder

Name: MCP Server Builder
Author: zach-source

byzach-source

0•

API Development

Guides the development of high-quality Model Context Protocol (MCP) servers for seamless LLM integration with external services.

This skill provides a structured, four-phase workflow for building robust MCP servers in both Python (FastMCP) and TypeScript. It streamlines the entire development lifecycle—from deep research and protocol compliance to implementation and rigorous evaluation. By focusing on well-designed tool schemas, actionable error messages, and standardized naming conventions, this skill ensures that developers can create reliable bridges between AI models and external APIs, enabling agents to perform complex, real-world tasks with precision.

Key Features

01Comprehensive patterns for tool naming, discoverability, and context management

02Advanced schema definition support using Zod and Pydantic for structured data

03Step-by-step implementation guides for Python and TypeScript SDKs

04Built-in evaluation framework for testing LLM tool-calling effectiveness

05Reference library for transport mechanisms including stdio and streamable HTTP

060 GitHub stars

Use Cases

01Standardizing tool interfaces for complex cross-platform developer workflows

02Creating and verifying production-grade MCP servers with automated evaluations

03Building custom API connectors to expose internal services to AI agents

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zach-source/claude-plugins mcp-builder

For use in Claude.ai and ChatGPT

Download Skill