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Agent Skill · 研究检索

build-mcp-server(构建 MCP server)

build-mcp-server 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。

build-mcp-server 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,权限为接触敏感数据;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 37,406。

总安装 1,740周安装 74GitHub Stars 131下载 610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:build-mcp-server(构建 MCP server)
来源仓库:https://github.com/pproenca/dot-skills
仓库路径:skills/build-mcp-server
安装命令:
npx skills add https://github.com/pproenca/dot-skills --skill build-mcp-server
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/pproenca/dot-skills --skill build-mcp-server

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。

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词或任务场景快速定位候选结果时使用。适用于构建 MCP server 相关的信息查询与整理,可结合来源仓库进一步核验用法。

通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和维护状态。安装前建议检查是否会触发联网、命令执行或文件读写,确保操作边界清晰。build-mcp-server 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/build-mcp-server

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/pproenca/dot-skills --skill build-mcp-server;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

    它需要接触敏感数据,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

build-mcp-server 怎么安装?

在终端执行 npx skills add https://github.com/pproenca/dot-skills --skill build-mcp-server。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

build-mcp-server 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。

build-mcp-server 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

build-mcp-server 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。

build-mcp-server 用的人多吗?

公开数据是累计安装 1,740 次,近一周安装 74 次,下载 610 次,GitHub 131 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。

build-mcp-server 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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
build-mcp-server

构建 MCP server · 本页

1,740131接触敏感数据未明确有提醒

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

Build an MCP Server

You are guiding a developer through designing and building an MCP server that works seamlessly with Claude. MCP servers come in many forms — picking the wrong shape early causes painful rewrites later. Your first job is discovery, not code.

Do not start scaffolding until you have answers to the questions in Phase 1. If the user's opening message already answers them, acknowledge that and skip straight to the recommendation.

When to Apply

  • User asks to build, create, or scaffold an MCP server
  • User wants to wrap a REST/GraphQL API for use with Claude
  • User wants to expose tools, resources, or prompts via MCP
  • User is choosing between deployment models (remote HTTP, MCPB, local stdio)
  • User is designing tool schemas for an MCP integration

Workflow Overview

Phase 1: Discovery → Phase 2: Deployment model → Phase 3: Tool pattern → Phase 4: Framework → Phase 5: Scaffold

Each phase narrows the design space. After Phase 5, hand off to the appropriate scaffold reference or companion skill.

Prerequisites

  • TypeScript path: Node.js >= 18, npm
  • Python path: Python >= 3.10, pip
  • Testing: npx (ships with npm) — used by scripts/test-server.sh and the MCP Inspector

Phase 1 — Interrogate the use case

Ask these questions conversationally (batch them into one message, don't interrogate one-at-a-time). Adapt wording to what the user has already told you.

1. What does it connect to?

If it connects to…Likely direction
A cloud API (SaaS, REST, GraphQL)Remote HTTP server
A local process, filesystem, or desktop appMCPB or local stdio
Hardware, OS-level APIs, or user-specific stateMCPB
Nothing external — pure logic / computationEither — default to remote

2. Who will use it?

  • Just me / my team, on our machines → Local stdio is acceptable (easiest to prototype)
  • Anyone who installs it → Remote HTTP (strongly preferred) or MCPB (if it *must* be local)
  • Users of Claude desktop who want UI widgets → MCP app (remote or MCPB)

3. How many distinct actions does it expose?

This determines the tool-design pattern — see Phase 3.

  • Under ~15 actions → one tool per action
  • Dozens to hundreds of actions (e.g. wrapping a large API surface) → search + execute pattern

4. Does a tool need mid-call user input or rich display?

  • Simple structured input (pick from list, enter a value, confirm) → Elicitation — spec-native, zero UI code. *Host support is rolling out* (Claude Code ≥2.1.76) — always pair with a capability check and fallback. See references/elicitation.md.
  • Rich/visual UI (charts, custom pickers with search, live dashboards) → MCP app widgets — iframe-based, needs @modelcontextprotocol/ext-apps. See build-mcp-app skill.
  • Neither → plain tool returning text/JSON.

5. What auth does the upstream service use?

  • None / API key → straightforward
  • OAuth 2.0 → you'll need a remote server with CIMD (preferred) or DCR support; see references/auth.md

Phase 2 — Recommend a deployment model

Based on the answers, recommend one path. Be opinionated. The ranked options:

Remote streamable-HTTP MCP server (default recommendation)

A hosted service speaking MCP over streamable HTTP. This is the recommended path for anything wrapping a cloud API.

Why it wins:

  • Zero install friction — users add a URL, done
  • One deployment serves all users; you control upgrades
  • OAuth flows work properly (the server can handle redirects, DCR, token storage)
  • Works across Claude desktop, Claude Code, Claude.ai, and third-party MCP hosts

Choose this unless the server *must* touch the user's local machine.

→ Fastest deploy: Cloudflare Workers — references/deploy-cloudflare-workers.md (zero to live URL in two commands) → Portable Node/Python: references/remote-http-scaffold.md (Express or FastMCP, runs on any host)

Elicitation (structured input, no UI build)

If a tool just needs the user to confirm, pick an option, or fill a short form, elicitation does it with zero UI code. The server sends a flat JSON schema; the host renders a native form. Spec-native, no extra packages.

Caveat: Host support is new (Claude Code shipped it in v2.1.76; Desktop unconfirmed). The SDK throws if the client doesn't advertise the capability. Always check clientCapabilities.elicitation first and have a fallback — see references/elicitation.md for the canonical pattern. This is the right spec-correct approach; host coverage will catch up.

Escalate to build-mcp-app widgets when you need: nested/complex data, scrollable/searchable lists, visual previews, live updates.

MCP app (remote HTTP + interactive UI)

Same as above, plus UI resources — interactive widgets rendered in chat. Rich pickers with search, charts, live dashboards, visual previews. Built once, renders in Claude *and* ChatGPT.

Choose this when elicitation's flat-form constraints don't fit — you need custom layout, large searchable lists, visual content, or live updates.

Usually remote, but can be shipped as MCPB if the UI needs to drive a local app.

→ Hand off to the build-mcp-app skill.

MCPB (bundled local server)

A local MCP server packaged with its runtime so users don't need Node/Python installed. The sanctioned way to ship local servers.

Choose this when the server *must* run on the user's machine — it reads local files, drives a desktop app, talks to localhost services, or needs OS-level access.

→ Hand off to the build-mcpb skill.

Local stdio (npx / uvx) — *not recommended for distribution*

A script launched via npx / uvx on the user's machine. Fine for personal tools and prototypes. Painful to distribute: users need the right runtime, you can't push updates, and the only distribution channel is Claude Code plugins.

Recommend this only as a stepping stone. If the user insists, scaffold it but note the MCPB upgrade path.


Phase 3 — Pick a tool-design pattern

Every MCP server exposes tools. How you carve them matters more than most people expect — tool schemas land directly in Claude's context window.

Pattern A: One tool per action (small surface)

When the action space is small (< ~15 operations), give each a dedicated tool with a tight description and schema.

create_issue    — Create a new issue. Params: title, body, labels[]
update_issue    — Update an existing issue. Params: id, title?, body?, state?
search_issues   — Search issues by query string. Params: query, limit?
add_comment     — Add a comment to an issue. Params: issue_id, body

Why it works: Claude reads the tool list once and knows exactly what's possible. No discovery round-trips. Each tool's schema validates inputs precisely.

Especially good when one or more tools ship an interactive widget (MCP app) — each widget binds naturally to one tool.

Pattern B: Search + execute (large surface)

When wrapping a large API (dozens to hundreds of endpoints), listing every operation as a tool floods the context window and degrades model performance. Instead, expose two tools:

search_actions  — Given a natural-language intent, return matching actions
                  with their IDs, descriptions, and parameter schemas.
execute_action  — Run an action by ID with a params object.

The server holds the full catalog internally. Claude searches, picks, executes. Context stays lean.

Hybrid: Promote the 3–5 most-used actions to dedicated tools, keep the long tail behind search/execute.

→ See references/tool-design.md for schema examples and description-writing guidance.


Phase 4 — Pick a framework

Recommend one of these two. Others exist but these have the best MCP-spec coverage and Claude compatibility.

FrameworkLanguageUse when
Official TypeScript SDK (@modelcontextprotocol/sdk)TS/JSDefault choice. Best spec coverage, first to get new features.
FastMCP 3.x (fastmcp on PyPI)PythonUser prefers Python, or wrapping a Python library. Decorator-based, very low boilerplate. This is jlowin's package — not the frozen FastMCP 1.0 bundled in the official mcp SDK.

If the user already has a language/stack in mind, go with it — both produce identical wire protocol.


Phase 5 — Scaffold and hand off

Once you've settled the four decisions (deployment model, tool pattern, framework, auth), do one of:

  1. Remote HTTP, no UI → Scaffold inline using references/remote-http-scaffold.md (portable) or references/deploy-cloudflare-workers.md (fastest deploy). This skill can finish the job.
  2. MCP app (UI widgets) → Summarize the decisions so far, then load the build-mcp-app skill.
  3. MCPB (bundled local) → Summarize the decisions so far, then load the build-mcpb skill.
  4. Local stdio prototype → Scaffold inline (simplest case), flag the MCPB upgrade path.

When handing off, restate the design brief in one paragraph so the next skill doesn't re-ask.

Verify the server

After scaffolding, verify the server responds correctly:

# Start the server first (e.g. npx tsx src/server.ts or python server.py)
# Then smoke-test it:
bash scripts/test-server.sh http://localhost:3000/mcp

The test script calls tools/list via the MCP Inspector and checks the server returns at least one tool. If this passes, the server is wired correctly.


Beyond tools — the other primitives

Tools are one of three server primitives. Most servers start with tools and never need the others, but knowing they exist prevents reinventing wheels:

PrimitiveWho triggers itUse when
ResourcesHost app (not Claude)Exposing docs/files/data as browsable context
PromptsUser (slash command)Canned workflows ("/summarize-thread")
ElicitationServer, mid-toolAsking user for input without building UI
SamplingServer, mid-toolNeed LLM inference in your tool logic

→ references/resources-and-prompts.md, references/elicitation.md, references/server-capabilities.md


Quick reference: decision matrix

ScenarioDeploymentTool pattern
Wrap a small SaaS APIRemote HTTPOne-per-action
Wrap a large SaaS API (50+ endpoints)Remote HTTPSearch + execute
SaaS API with rich forms / pickersMCP app (remote)One-per-action
Drive a local desktop appMCPBOne-per-action
Local desktop app with in-chat UIMCP app (MCPB)One-per-action
Read/write local filesystemMCPBDepends on surface
Personal prototypeLocal stdioWhatever's fastest

Reference files

Read these when you reach the relevant phase — not upfront:

平台分布

Codex

37.25%
按下载量换算227

Claude

28.87%
按下载量换算176

Cursor

19.41%
按下载量换算118

Gemini CLI

10.77%
按下载量换算66

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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