How does this help with tool discoverability?

It provides standardized naming conventions and description patterns that help LLMs accurately identify and select the correct tool for a given task.

Can I use this for both local and remote MCP servers?

Yes, the guide covers implementation for both stdio transport (local) and streamable HTTP transport (remote/stateless) architectures.

What programming languages are supported for MCP development?

This skill provides detailed guidance and SDK support for both TypeScript (Node.js) and Python (including FastMCP).

What is the purpose of the evaluation phase?

The evaluation phase helps you create complex, realistic test cases in XML format to verify that an LLM can successfully use your MCP tools to solve real-world problems.

Does it support data validation?

Absolutely. It promotes using Zod for TypeScript and Pydantic for Python to ensure strict input/output schema validation for all tools.

MCP Server Builder

Name: MCP Server Builder
Author: NaveedTechLab

byNaveedTechLab

API Development

Guides the development of high-quality Model Context Protocol (MCP) servers to connect Claude with external APIs and services.

About

The MCP Server Builder skill provides a comprehensive architectural framework for creating robust Model Context Protocol integrations. It streamlines the development lifecycle by offering domain-specific guidance on tool design, schema definition using Zod or Pydantic, and implementation patterns for both TypeScript and Python. Whether you are building local tools via stdio or remote services via HTTP, this skill ensures your MCP servers are optimized for agentic discovery, efficient context management, and rigorous evaluation, ultimately enabling Claude to interact seamlessly with any external data source or software service.

Key Features

0 GitHub stars
Best practices for tool naming, discoverability, and context management
Comprehensive evaluation framework for verifying LLM tool performance
Language-specific implementation patterns for TypeScript SDK and Python FastMCP
Support for Zod and Pydantic schema validation and structured tool outputs
Standardized error handling and actionable messaging strategies

Use Cases

Building and running evaluation suites to ensure high reliability of AI tool calls
Developing custom MCP servers to integrate internal company databases with Claude
Creating standardized API wrappers that allow AI agents to execute complex workflows

About

Key Features

0 GitHub stars
Best practices for tool naming, discoverability, and context management
Comprehensive evaluation framework for verifying LLM tool performance
Language-specific implementation patterns for TypeScript SDK and Python FastMCP
Support for Zod and Pydantic schema validation and structured tool outputs
Standardized error handling and actionable messaging strategies

Use Cases

Building and running evaluation suites to ensure high reliability of AI tool calls
Developing custom MCP servers to integrate internal company databases with Claude
Creating standardized API wrappers that allow AI agents to execute complex workflows