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mcp-builder

Build production-ready MCP servers enabling LLMs to integrate external APIs using TypeScript or Python with comprehensive testing and evaluation guidelines.

12.4k次下载·110.3k个收藏
A
作者: anthropics

关于此技能

Poorly designed MCP servers fail when agents attempt complex tasks, wasting development time on broken integrations. This skill guides you through four phases of research, implementation, and testing using TypeScript or Python SDKs. You receive specific patterns for tool schemas, error handling, and creating verifiable evaluations to ensure reliability. Use this when building integrations that require robust, agent-ready tools for external APIs.

5 分钟完成安装

复制以下提示词,粘贴到 OpenClaw 中即可自动安装:

请根据 https://clawshelf.com/api/skills/anthropics-mcp-builder/install 的说明,下载并安装此技能到本地 ~/.openclaw/skills/ 目录。

文件预览

包含文件

  • SKILL.md
SKILL.md
---
name: mcp-builder
description: Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
license: Complete terms in LICENSE.txt
---

# MCP Server Development Guide

## Overview

Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.

---

# Process

## 🚀 High-Level Workflow

Creating a high-quality MCP server involves four main phases:

### Phase 1: Deep Research and Planning

#### 1.1 Understand Modern MCP Design

**API Coverage vs. Workflow Tools:**
Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.

**Tool Naming and Discoverability:**
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming.

**Context Management:**
Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.

**Actionable Error Messages:**
Error messages should guide agents toward solutions with specific suggestions and next steps.

#### 1.2 Study MCP Protocol Documentation

**Navigate the MCP specification:**

Start with the sitemap to find relevant pages: `htt

搭配使用

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$0

一次购买 · 终身更新

100% 原生支持 OpenClaw / Claude 等任何 AI 助手

创作者
A
anthropics
类型技能
分类development
价格$0
上架时间3/29/2026
授权一次性购买
下载量12,435
收藏量110,272
版本1.0.0
来源github.com
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