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FelipeMaines
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mcp-builder

Plan and implement MCP servers for Python or TypeScript with validated tools.

Updated May 25, 2026
Search Tags:#evaluation#mcp#api integration#model context protocol#tool design#python fastmcp#typescript mcp sdk
One-click install
npx skills add https://github.com/FelipeMaines/ProjetoWeb --skill mcp-builder-felipemaines
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mcp-builder
Source: https://github.com/FelipeMaines/ProjetoWeb/tree/main/.claude/skills/mcp-builder
Command: npx skills add https://github.com/FelipeMaines/ProjetoWeb --skill mcp-builder-felipemaines

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you design and implement high-quality MCP (Model Context Protocol) servers so LLM agents can reliably call tools to complete real tasks using external services.

Core Features & Use Cases

  • Workflow-first tool design: Build tool interfaces around complete agent workflows rather than thin API wrappers.
  • Agent-context optimization: Reduce wasted tokens by returning high-signal, human-readable or structured outputs with truncation strategies.
  • LLM-friendly robustness: Create clear, actionable, educational error messages and predictable schemas for inputs and outputs.
  • Implementation guidance across ecosystems: Apply best practices for both Python (FastMCP) and Node/TypeScript MCP SDK.
  • Evaluation-driven improvement loop: Define realistic, read-only evaluations to measure whether agents can actually use your tools effectively.

Quick Start

Use the mcp-builder skill to produce an MCP server plan for integrating an external API, then follow the Python or TypeScript implementation guide to register validated tools.

Frequently Asked Questions about mcp-builder

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

FAQPage Schema
How do I design Model Context Protocol servers for LLM agents to use external APIs?▼

Design Model Context Protocol servers by building workflow-focused tool interfaces rather than thin API wrappers, ensuring LLM agents receive high-signal structured outputs with clear truncation strategies and actionable error messages.

How does the evaluation-driven process improve MCP tool design?▼

The evaluation-driven process improves MCP tool design by defining realistic, read-only question suites that measure whether agents can actually use your tools effectively, ensuring correctness before final implementation.

Can I build MCP servers using both Python FastMCP and TypeScript SDKs?▼

You can build MCP servers using both Python FastMCP and Node TypeScript SDKs, applying implementation best practices for registering validated tools and designing predictable input and output schemas across both ecosystems.

What is the best way to handle pagination and truncation in MCP tool outputs?▼

Handle pagination and truncation in MCP tool outputs by applying agent-context optimization strategies that reduce wasted tokens, returning high-signal human-readable or structured data to LLM agents.

Why should I build workflow-focused tool interfaces instead of thin API wrappers for MCP?▼

Workflow-focused tool interfaces let LLM agents complete real tasks through external services by mapping complete agent workflows, whereas thin API wrappers often return low-signal data that wastes tokens and degrades reliability.

Do I need to study API documentation before implementing an MCP server?▼

You must study both the MCP protocol SDK documentation and perform exhaustive API research before implementing an MCP server, as this ensures correctness in your tool naming, schemas, and error handling.

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