How does mcp-builder help with tool discoverability?

It enforces consistent naming conventions, descriptive schemas, and context management patterns that help LLMs identify the right tool for a specific task more accurately.

Does this skill support both local and remote MCP servers?

Yes, it includes guidance for both stdio (typically used for local servers) and streamable HTTP (used for remote, scalable server deployments).

What is the primary purpose of the mcp-builder skill?

It provides a standardized methodology and technical guidance for building servers that follow the Model Context Protocol, allowing AI models to use external tools and data safely.

What is the 'Evaluation Phase' mentioned in the guide?

It is a quality control process where you create 10 complex, realistic questions and verifiable answers to test if the LLM can successfully navigate your MCP tools.

Can I use this for Python-based development?

Absolutely. The skill includes a dedicated Python Implementation Guide focusing on the FastMCP framework and Pydantic-based data modeling.

MCP Server Builder

Name: MCP Server Builder
Author: feed-mob

byfeed-mob

API開発

Streamlines the development of Model Context Protocol (MCP) servers with standardized patterns for TypeScript and Python integrations.

概要

The mcp-builder skill is a comprehensive framework and development guide designed to help developers create production-grade MCP servers. It provides a structured, four-phase workflow—covering research, implementation, testing, and evaluation—to ensure that LLMs can effectively interact with external services. By offering domain-specific guidance for both the TypeScript SDK and Python's FastMCP, this skill simplifies complex tasks like tool discovery, context management, and structured error handling, making it an essential resource for extending AI capabilities through external API integrations.

主な機能

Step-by-step implementation guides for core infrastructure and shared utilities
Multi-language support for TypeScript (Node.js) and Python (FastMCP) SDKs
0 GitHub stars
Best practices for pagination, context management, and actionable error messages
Standardized tool naming and discoverability patterns for improved LLM performance
Integrated evaluation framework for verifying tool effectiveness with complex Q&A

ユースケース

Architecting a custom MCP server to bridge internal company data with Claude Code
Creating automated evaluation suites to benchmark LLM tool-calling accuracy
Implementing standardized tool schemas using Zod or Pydantic for robust API interaction

概要

主な機能

Step-by-step implementation guides for core infrastructure and shared utilities
Multi-language support for TypeScript (Node.js) and Python (FastMCP) SDKs
0 GitHub stars
Best practices for pagination, context management, and actionable error messages
Standardized tool naming and discoverability patterns for improved LLM performance
Integrated evaluation framework for verifying tool effectiveness with complex Q&A

ユースケース

Architecting a custom MCP server to bridge internal company data with Claude Code
Creating automated evaluation suites to benchmark LLM tool-calling accuracy
Implementing standardized tool schemas using Zod or Pydantic for robust API interaction