What is the recommended transport for remote servers?

The guide recommends streamable HTTP using stateless JSON for remote servers to ensure easier scaling and maintenance.

How does mcp-builder help with testing LLM performance?

It includes a dedicated evaluation phase that guides you through creating 10 complex, realistic questions and answers in a standardized XML format to verify tool accuracy.

What programming languages does mcp-builder support?

It provides detailed patterns and SDK documentation for both TypeScript/Node.js and Python (using FastMCP).

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

Yes, the skill covers implementation for both stdio (standard input/output) for local use and streamable HTTP for remote deployments.

Does it provide templates for tool definitions?

Yes, it includes specific guidance on using Zod (TypeScript) or Pydantic (Python) to define input/output schemas and context hints.

MCP Server Builder

Name: MCP Server Builder
Author: nijjaraerp

bynijjaraerp

API Development

Builds high-quality Model Context Protocol (MCP) servers to connect external APIs and services with LLMs.

About

The mcp-builder skill provides a comprehensive framework and standardized process for developing Model Context Protocol (MCP) servers in both Python and TypeScript. It guides users through deep research, implementation of core infrastructure, tool design with proper schema annotations, and the creation of robust evaluation suites to ensure LLMs can effectively utilize the server. This skill is essential for developers looking to extend Claude's capabilities by integrating custom external services with reliable, well-documented tools and actionable error handling.

Key Features

Best practice alignment for transport protocols like stdio and streamable HTTP
Guided workflow for Python (FastMCP) and TypeScript (MCP SDK) development
Standardized tool naming and context management patterns
Zod and Pydantic schema implementation for structured data input/output
Built-in evaluation methodology for testing LLM tool-calling performance
0 GitHub stars

Use Cases

Creating custom internal API integrations for LLM-based agents
Standardizing MCP server development across engineering teams
Benchmarking and evaluating the reliability of tool-calling for specific domains

About

Key Features

Best practice alignment for transport protocols like stdio and streamable HTTP
Guided workflow for Python (FastMCP) and TypeScript (MCP SDK) development
Standardized tool naming and context management patterns
Zod and Pydantic schema implementation for structured data input/output
Built-in evaluation methodology for testing LLM tool-calling performance
0 GitHub stars

Use Cases

Creating custom internal API integrations for LLM-based agents
Standardizing MCP server development across engineering teams
Benchmarking and evaluating the reliability of tool-calling for specific domains