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mcp-builder

Build Model Context Protocol servers with Python FastMCP and Node/TypeScript SDKs.

2|1|Updated Apr 4, 2026
Search Tags:#typescript#evaluation#mcp#api-integration#tool-design#fastmcp#server-development
One-click install
npx skills add https://github.com/stefantrajanov/mk-data-mcp --skill mcp-builder-stefantrajanov
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mcp-builder
Source: https://github.com/stefantrajanov/mk-data-mcp/tree/main/.agents/skills/mcp-builder
Command: npx skills add https://github.com/stefantrajanov/mk-data-mcp --skill mcp-builder-stefantrajanov

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, mcp, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Creating MCP servers traditionally requires scattered research across protocol specs, SDK documentation, and community best practices, leading to inconsistent tool designs and poor LLM interoperability. This skill consolidates authoritative guidance into a single, structured workflow that ensures your MCP server is production-ready, well-documented, and thoroughly evaluated for real-world agent tasks.

Core Features & Use Cases

  • Dual-Language Implementation Paths: Complete setup guides for both Python (FastMCP) and Node/TypeScript (MCP SDK), including project structure, dependency management, and transport configuration.
  • Tool Design & Validation: Patterns for creating discoverable, type-safe tools with Zod/Pydantic schemas, actionable error messages, pagination support, and proper annotations.
  • Evaluation & Testing: Built-in harness for generating complex evaluation questions, running them against your server, and producing detailed accuracy reports to validate LLM effectiveness.

Quick Start

Use the mcp-builder skill to develop a new MCP server by following the four-phase process—research, implement, test, and evaluate—using the provided reference materials and script templates.

Frequently Asked Questions about mcp-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a production-ready MCP server for AI agents?▼

You can develop MCP servers using either Python FastMCP or Node TypeScript SDK stacks, with complete setup guides for project structure, dependency management, and transport configuration. This dual-language implementation path ensures you can build standardized tools using your preferred technology stack.

What is the best way to design tools with input validation for an MCP server?▼

You can validate LLM effectiveness by using a built-in evaluation harness that generates complex evaluation questions and runs them against your MCP server. This testing framework produces detailed accuracy reports using XML-based test generation to ensure real-world agent task readiness.

Does the MCP server development workflow support both Python and TypeScript?▼

You can validate LLM effectiveness by using a built-in evaluation harness that generates complex evaluation questions and runs them against your MCP server. This testing framework produces detailed accuracy reports using XML-based test generation to ensure real-world agent task readiness.

How do I test and evaluate an MCP server for real-world agent tasks?▼

You can validate LLM effectiveness by using a built-in evaluation harness that generates complex evaluation questions and runs them against your MCP server. This testing framework produces detailed accuracy reports using XML-based test generation to ensure real-world agent task readiness.

Why do I need standardized tool design and error handling in Model Context Protocol servers?▼

You can validate LLM effectiveness by using a built-in evaluation harness that generates complex evaluation questions and runs them against your MCP server. This testing framework produces detailed accuracy reports using XML-based test generation to ensure real-world agent task readiness.

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