mcp-builder

Creates MCP servers for Python FastMCP and Node.js/TypeScript with validation and evaluation XML.

Updated May 28, 2026

Search Tags:#mcp #api integration #tool design #agent workflows #python fastmcp #typescript mcp sdk

Ready to run

npx skills add https://github.com/GustaPaes/aiox-sprint-canvas --skill mcp-builder-gustapaes

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mcp-builder
Source: https://github.com/GustaPaes/aiox-sprint-canvas/tree/main/.claude/skills/mcp-builder
Command: npx skills add https://github.com/GustaPaes/aiox-sprint-canvas --skill mcp-builder-gustapaes

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you design and implement MCP (Model Context Protocol) servers so LLMs can reliably use tools to perform real, end-to-end tasks through external services and APIs.

Core Features & Use Cases

Workflow-oriented tool design: builds tools around complete actions and agent workflows rather than thin API wrappers.
LLM-efficient interfaces: optimizes inputs/outputs for limited context, includes concise vs detailed output strategies, and uses human-friendly identifiers.
Protocol-quality engineering: provides structured guidance for schemas, actionable error messages, annotations, safe testing, and evaluation planning.

Quick Start

Ask an AI assistant to turn your target external API into an MCP server plan that includes tool list, input/output schemas, error handling strategy, and a set of 10 evaluation questions.

Frequently Asked Questions about mcp-builder

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

FAQPage Schema

How do I design an MCP server for LLM agent workflows?▼

Designing an MCP server for agent workflows involves building tools around complete actions rather than thin API wrappers, optimizing inputs and outputs for limited LLM context, and validating tool schemas for safe API integration.

What is the best way to expose an external API to LLMs using Model Context Protocol?▼

The best way to expose external APIs via Model Context Protocol is to implement well-designed tools with validated schemas, actionable LLM-friendly error messages, and concise output strategies tailored to limited context windows.

Can I use Python FastMCP and TypeScript MCP SDK to build tools for agent workflows?▼

Yes, you can use Python FastMCP or the TypeScript MCP SDK to implement servers, applying protocol-quality engineering for schema validation, safe testing, and evaluation XML generation to integrate external services.

How does tool schema validation work when building MCP servers?▼

Tool schema validation ensures MCP servers process inputs safely by enforcing structured API schemas, generating actionable LLM-friendly errors for failed operations, and providing annotations for transport-aware testing.

Why does my LLM fail to use external API tools efficiently during agent workflows?▼

LLMs fail to use external API tools efficiently when servers use thin API wrappers instead of workflow-oriented tools, causing context bloat from verbose outputs and non-actionable error messages.

Do I need to generate evaluation questions when testing MCP server implementations?▼

Yes, generating evaluation questions and XML outputs is required to assess MCP server implementations, ensuring tools perform real end-to-end tasks safely and efficiently through transport-aware testing protocols.