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.

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

01Comprehensive workflows for TypeScript (SDK) and Python (FastMCP) implementations.

02Rigorous evaluation framework for testing tool effectiveness with realistic QA pairs.

03Standardized schema design patterns using Zod and Pydantic for input validation.

043 GitHub stars

05Guidance on implementing actionable error messages and pagination support.

06Best practices for tool naming, discoverability, and context management.

Use Cases

01Creating standardized API wrappers for third-party services like GitHub, Slack, or Jira.

02Building custom MCP servers to connect internal databases or legacy systems to Claude.

03Developing production-grade LLM tools with built-in evaluation and testing suites.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add daisuke134/anicca.ai mcp-builder

For use in Claude.ai and ChatGPT

Download Skill