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Agent Skill · 研究检索

mcp-builder-ms(MCP 构建器 MS)

mcp-builder-ms 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

mcp-builder-ms 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 37,733。

总安装 1,680周安装 70GitHub Stars 35,715下载 560核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mcp-builder-ms(MCP 构建器 MS)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/mcp-builder-ms
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill mcp-builder-ms
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill mcp-builder-ms

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

mcp-builder-ms 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中筛选信息的场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态及是否触发联网或文件操作。建议结合原始 README 和仓库内容进一步核验具体用法。

来源仓库内路径:skills/mcp-builder-ms

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill mcp…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

mcp-builder-ms 怎么安装?

在终端执行 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill mcp-builder-m…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

mcp-builder-ms 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

mcp-builder-ms 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

mcp-builder-ms 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

mcp-builder-ms 用的人多吗?

公开数据是累计安装 1,680 次,近一周安装 70 次,下载 560 次,GitHub 35,715 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

mcp-builder-ms 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 35,715 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
mcp-builder-ms

MCP 构建器 MS · 本页

1,68035,715操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

MCP Server Development Guide

When to Use

Use this skill when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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.


Microsoft MCP Ecosystem

Microsoft provides extensive MCP infrastructure for Azure and Foundry services. Understanding this ecosystem helps you decide whether to build custom servers or leverage existing ones.

Server Types

TypeTransportUse CaseExample
LocalstdioDesktop apps, single-user, local devAzure MCP Server via NPM/Docker
RemoteStreamable HTTPCloud services, multi-tenant, Agent Servicehttps://mcp.ai.azure.com (Foundry)

Microsoft MCP Servers

Before building a custom server, check if Microsoft already provides one:

ServerTypeDescription
Azure MCPLocal48+ Azure services (Storage, KeyVault, Cosmos, SQL, etc.)
Foundry MCPRemotehttps://mcp.ai.azure.com - Models, deployments, evals, agents
Fabric MCPLocalMicrosoft Fabric APIs, OneLake, item definitions
Playwright MCPLocalBrowser automation and testing
GitHub MCPRemotehttps://api.githubcopilot.com/mcp

Full ecosystem: See 🔷 Microsoft MCP Patterns for complete server catalog and patterns.

When to Use Microsoft vs Custom

ScenarioRecommendation
Azure service integrationUse Azure MCP Server (48 services covered)
AI Foundry agents/evalsUse Foundry MCP remote server
Custom internal APIsBuild custom server (this guide)
Third-party SaaS integrationBuild custom server (this guide)
Extending Azure MCPFollow Microsoft MCP Patterns

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: https://modelcontextprotocol.io/sitemap.xml

Then fetch specific pages with .md suffix for markdown format (e.g., https://modelcontextprotocol.io/specification/draft.md).

Key pages to review:

  • Specification overview and architecture
  • Transport mechanisms (streamable HTTP, stdio)
  • Tool, resource, and prompt definitions
1.3 Study Framework Documentation

Language Selection:

LanguageBest ForSDK
TypeScript (recommended)General MCP servers, broad compatibility@modelcontextprotocol/sdk
PythonData/ML pipelines, FastAPI integrationmcp (FastMCP)
C#/.NETAzure/Microsoft ecosystem, enterpriseMicrosoft.Mcp.Core

Transport Selection:

TransportUse CaseCharacteristics
Streamable HTTPRemote servers, multi-tenant, Agent ServiceStateless, scalable, requires auth
stdioLocal servers, desktop appsSimple, single-user, no network

Load framework documentation:

  • MCP Best Practices: 📋 View Best Practices - Core guidelines

For TypeScript (recommended):

  • TypeScript SDK: Use WebFetch to load https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md
  • ⚡ TypeScript Guide - TypeScript patterns and examples

For Python:

  • Python SDK: Use WebFetch to load https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md
  • 🐍 Python Guide - Python patterns and examples

For C#/.NET (Microsoft ecosystem):

  • 🔷 Microsoft MCP Patterns - C# patterns, Azure MCP architecture, command hierarchy
1.4 Plan Your Implementation

Understand the API: Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed.

Tool Selection: Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations.


Phase 2: Implementation

2.1 Set Up Project Structure

See language-specific guides for project setup:

  • ⚡ TypeScript Guide - Project structure, package.json, tsconfig.json
  • 🐍 Python Guide - Module organization, dependencies
  • 🔷 Microsoft MCP Patterns - C# project structure, command hierarchy
2.2 Implement Core Infrastructure

Create shared utilities:

  • API client with authentication
  • Error handling helpers
  • Response formatting (JSON/Markdown)
  • Pagination support
2.3 Implement Tools

For each tool:

Input Schema:

  • Use Zod (TypeScript) or Pydantic (Python)
  • Include constraints and clear descriptions
  • Add examples in field descriptions

Output Schema:

  • Define outputSchema where possible for structured data
  • Use structuredContent in tool responses (TypeScript SDK feature)
  • Helps clients understand and process tool outputs

Tool Description:

  • Concise summary of functionality
  • Parameter descriptions
  • Return type schema

Implementation:

  • Async/await for I/O operations
  • Proper error handling with actionable messages
  • Support pagination where applicable
  • Return both text content and structured data when using modern SDKs

Annotations:

  • readOnlyHint: true/false
  • destructiveHint: true/false
  • idempotentHint: true/false
  • openWorldHint: true/false

Phase 3: Review and Test

3.1 Code Quality

Review for:

  • No duplicated code (DRY principle)
  • Consistent error handling
  • Full type coverage
  • Clear tool descriptions
3.2 Build and Test

TypeScript:

  • Run npm run build to verify compilation
  • Test with MCP Inspector: npx @modelcontextprotocol/inspector

Python:

  • Verify syntax: python -m py_compile your_server.py
  • Test with MCP Inspector

See language-specific guides for detailed testing approaches and quality checklists.


Phase 4: Create Evaluations

After implementing your MCP server, create comprehensive evaluations to test its effectiveness.

Load ✅ Evaluation Guide for complete evaluation guidelines.

4.1 Understand Evaluation Purpose

Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions.

4.2 Create 10 Evaluation Questions

To create effective evaluations, follow the process outlined in the evaluation guide:

  1. Tool Inspection: List available tools and understand their capabilities
  2. Content Exploration: Use READ-ONLY operations to explore available data
  3. Question Generation: Create 10 complex, realistic questions
  4. Answer Verification: Solve each question yourself to verify answers
4.3 Evaluation Requirements

Ensure each question is:

  • Independent: Not dependent on other questions
  • Read-only: Only non-destructive operations required
  • Complex: Requiring multiple tool calls and deep exploration
  • Realistic: Based on real use cases humans would care about
  • Verifiable: Single, clear answer that can be verified by string comparison
  • Stable: Answer won't change over time
4.4 Output Format

Create an XML file with this structure:

<evaluation>
  <qa_pair>
    <question>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?</question>
    <answer>3</answer>
  </qa_pair>
<!-- More qa_pairs... -->
</evaluation>

Reference Files

📚 Documentation Library

Load these resources as needed during development:

Core MCP Documentation (Load First)

  • MCP Protocol: Start with sitemap at https://modelcontextprotocol.io/sitemap.xml, then fetch specific pages with .md suffix
  • 📋 MCP Best Practices - Universal MCP guidelines including:

- Server and tool naming conventions - Response format guidelines (JSON vs Markdown) - Pagination best practices - Transport selection (streamable HTTP vs stdio) - Security and error handling standards

Microsoft MCP Documentation (For Azure/Foundry)

  • 🔷 Microsoft MCP Patterns - Microsoft-specific patterns including:

- Azure MCP Server architecture (48+ Azure services) - C#/.NET command implementation patterns - Remote MCP with Foundry Agent Service - Authentication (Entra ID, OBO flow, Managed Identity) - Testing infrastructure with Bicep templates

SDK Documentation (Load During Phase 1/2)

  • Python SDK: Fetch from https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md
  • TypeScript SDK: Fetch from https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md
  • Microsoft MCP SDK: See Microsoft MCP Patterns for C#/.NET

Language-Specific Implementation Guides (Load During Phase 2)

  • 🐍 Python Implementation Guide - Complete Python/FastMCP guide with:

- Server initialization patterns - Pydantic model examples - Tool registration with @mcp.tool - Complete working examples - Quality checklist

  • ⚡ TypeScript Implementation Guide - Complete TypeScript guide with:

- Project structure - Zod schema patterns - Tool registration with server.registerTool - Complete working examples - Quality checklist

  • 🔷 Microsoft MCP Patterns - Complete C#/.NET guide with:

- Command hierarchy (BaseCommand → GlobalCommand → SubscriptionCommand) - Naming conventions ({Resource}{Operation}Command) - Option handling with .AsRequired() / .AsOptional() - Azure Functions remote MCP deployment - Live test patterns with Bicep

Evaluation Guide (Load During Phase 4)

  • ✅ Evaluation Guide - Complete evaluation creation guide with:

- Question creation guidelines - Answer verification strategies - XML format specifications - Example questions and answers - Running an evaluation with the provided scripts

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

平台分布

Codex

37.17%
按下载量换算208

Claude

30.45%
按下载量换算171

Cursor

18.7%
按下载量换算105

Gemini CLI

9.51%
按下载量换算53

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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