原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Ncp

作者:portel-dev版本 3.0.0i★ –i在你的电脑上运行
注册名称io.github.portel-dev/ncp

安装

概览

作者提供的说明(英文原文)

1 MCP to rule them all. Orchestrate, discover, and run any tool instantly.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: NCP_DEBUG, NCP_MODE, NO_COLOR

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "ncp": {
      "command": "npx",
      "args": [
        "-y",
        "@portel/ncp"
      ],
      "env": {
        "NCP_DEBUG": "your-value",
        "NCP_MODE": "your-value",
        "NO_COLOR": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add ncp --env NCP_DEBUG=your-value --env NCP_MODE=your-value --env NO_COLOR=your-value -- npx -y @portel/ncp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "ncp": {
      "command": "npx",
      "args": [
        "-y",
        "@portel/ncp"
      ],
      "env": {
        "NCP_DEBUG": "your-value",
        "NCP_MODE": "your-value",
        "NO_COLOR": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "ncp": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@portel/ncp"
      ],
      "env": {
        "NCP_DEBUG": "your-value",
        "NCP_MODE": "your-value",
        "NO_COLOR": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • NCP_DEBUG env
    Enable debug logging for troubleshooting
  • NCP_MODE env
    Operating mode: 'mcp' for AI assistant integration or 'cli' for command-line
  • NO_COLOR env
    Disable colored output in logs and CLI

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 portel-dev 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32466 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32466 个服务器的 67% 更新
  • 基础检查结果等于或优于此分类中其他 32466 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Ncp 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(3.0.0)于18天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, HotCodePush

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

HotCodePush

作者:hotcodepush-team

Manage over-the-air (OTA) updates for React Native, Expo, Capacitor and Cordova apps.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

NCP - Natural Context Provider

1 MCP to rule them all

Your MCPs, supercharged. Discover tools, execute with code mode, run on schedule, find skills, and load Photons through common MCP clients. On-demand discovery keeps the initial tool surface focused.

Related Portel project: Photon turns TypeScript methods into reliable agent-facing capabilities: MCP tools, embedded app UIs, CLI commands, web routes, schedules, webhooks, retries, and Beam interfaces. NCP helps agents discover and operate tools; Photon helps developers build the tools and apps agents can trust.

💍 What is NCP?

Instead of your AI juggling 50+ tools scattered across different MCPs, NCP gives it a single, unified interface with code mode execution, scheduling, skills discovery, and custom Photons.

Most hosts see NCP's small gateway surface (find, run, and, when enabled, code). Hosts that support MCP Apps can also receive selected app callback tools so embedded interfaces keep working. NCP adds app tools selectively; it omits conflicting app groups rather than renaming callbacks that an app may call by name.

  • `find` - Search for any tool, skill, or Photon: "I need to read a file" → finds the right tool automatically
  • `code` - Execute TypeScript directly: await github.create_issue({...}) (code mode, enabled by default)
  • `run` - Execute tools individually (when code mode is disabled)

Behind the scenes, NCP manages all 50+ tools + skills + Photons: routing requests, discovering the right capability, executing code, scheduling tasks, managing health, and caching responses.

The host determines which optional features it can use. NCP advertises MCP Apps, Skills, and Tasks capabilities, while clients that do not support an extension continue with the core tools and existing request flows.

Why this matters:

  • Your AI stops analyzing "which tool do I use?" and starts doing actual work
  • Code mode lets AI write multi-step TypeScript workflows combining tools, skills, and scheduling
  • Skills provide domain expertise: canvas design, PDF manipulation, document generation, more
  • Photons enable custom TypeScript MCPs without npm publishing
  • On-demand discovery keeps the initial tool surface focused; actual context use depends on the host, enabled NCP tools, and connected servers
  • Your AI becomes focused. Not desperate.

🚀 NEW: Project-level configuration - each project can define its own MCPs automatically

What's MCP? The Model Context Protocol by Anthropic lets AI assistants connect to external tools and data sources. Think of MCPs as "plugins" that give your AI superpowers like file access, web search, databases, and more.


📑 Quick Navigation

  • The Problem - Why too many tools break your AI
  • The Solution - How NCP transforms your experience
  • Getting Started - Installation & quick start
  • Try It Out - See the CLI in action
  • Supercharged Features - How NCP empowers your MCPs
  • Setup by Client - Claude Desktop, Cursor, VS Code, etc.
  • Popular MCPs - Community favorites to add
  • Advanced Features - Project config, scheduling, remote MCPs
  • Troubleshooting - Common issues & solutions
  • How It Works - Technical deep dive
  • Contributing - Help us improve NCP

😤 The MCP Paradox: From Assistant to Desperate

You gave your AI assistant 50 tools to be more capable. Instead, you got desperation:

  • Paralyzed by choice ("Should I use read_file or get_file_content?")
  • Exhausted before starting ("I've spent my context limit analyzing which tool to use")
  • Costs explode (50+ tool schemas burn tokens before any real work happens)
  • Asks instead of acts (used to be decisive, now constantly asks for clarification)

🧸 Why Too Many Tools Break the System

Think about it like this:

A child with one toy → Treasures it, masters it, creates endless games with it A child with 50 toys → Can't hold them all, gets overwhelmed, stops playing entirely

Your AI is that child. MCPs are the toys. More isn't always better.

The most creative people thrive with constraints, not infinite options. A poet given "write about anything" faces writer's block. Given "write a haiku about rain"? Instant inspiration.

Your AI is the same. Give it one perfect tool → Instant action. Give it 50 tools → Cognitive overload. NCP provides just-in-time tool discovery so your AI gets exactly what it needs, when it needs it.


📊 The Before & After Reality

Before NCP: Desperate Assistant 😵💫

When your AI assistant manages 50 tools directly:

🤖 AI Assistant Context:

├── Filesystem MCP (12 tools) ├── Database MCP (8 tools) ├── Web Search MCP (6 tools) ├── Email MCP (15 tools) ├── Shell MCP (10 tools) ├── GitHub MCP (20 tools) └── Slack MCP (9 tools)

💀 Total: 80 tool schemas compete for attention before useful work begins

What happens:

  • AI burns 50%+ of context just understanding what tools exist
  • Spends 5-8 seconds analyzing which tool to use
  • Often picks wrong tool due to schema confusion
  • Hits context limits mid-conversation
After NCP: Executive Assistant ✨

With NCP as Chief of Staff:

🤖 AI Assistant Context:

└── NCP gateway tools → discover and run the tools needed for this request

🎯 Behind the scenes: NCP manages all 80 tools 📈 Tool discovery happens on demand 🎪 AI behavior: Confident, focused, decisive

NCP reduces the need to load every downstream tool schema into the host up front. The amount of context saved and any effect on response time vary with the host, server catalog, and enabled features.


📋 Prerequisites

  • Node.js 22+ (Node.js 24 recommended; CI uses 24) (Download here)
  • npm (included with Node.js) or npx for running packages
  • Command line access (Terminal on Mac/Linux, Command Prompt/PowerShell on Windows)

🚀 Installation

Choose your MCP client for setup instructions:

ClientDescriptionSetup Guide
Claude DesktopAnthropic's official desktop app. Best for NCP - one-click .dxt install with auto-sync[→ Full Guide](docs/clients/claude-desktop.md)
Claude CodeTerminal-first AI workflow. Works out of the box!Built-in support
VS CodeGitHub Copilot with Agent Mode. Use NCP for semantic tool discovery[→ Setup](docs/clients/vscode.md)
CursorAI-first code editor with Composer. Popular VS Code alternative[→ Setup](docs/clients/cursor.md)
WindsurfCodeium's AI-native IDE with Cascade. Built on VS Code[→ Setup](docs/clients/windsurf.md)
ClineVS Code extension for AI-assisted development with MCP support[→ Setup](docs/clients/cline.md)
ContinueVS Code AI assistant with Agent Mode and local LLM support[→ Setup](docs/clients/continue.md)
Want more clients?See the full list of MCP-compatible clients and toolsOfficial MCP Clients • Awesome MCP
Other ClientsAny MCP-compatible client via npmQuick Start ↓

Quick Start (npm)

For advanced users or MCP clients not listed above:

Step 1: Install NCP

npm install -g @portel/ncp

Step 2: Import existing MCPs (optional)

ncp config import  # Paste your config JSON when prompted

Step 3: Configure your MCP client

Add to your client's MCP configuration:

{

"mcpServers": { "ncp": { "command": "ncp" } } }

✅ Done! Your AI can discover and run tools through NCP. Hosts with MCP Apps support may also receive selected app callback tools.


🧪 Test Drive: See the Difference Yourself

Want to experience what your AI experiences? NCP has a human-friendly CLI:

🔍 Smart Discovery
# Ask like your AI would ask:

ncp find "I need to read a file" ncp find "help me send an email" ncp find "search for something online"

Notice: NCP understands intent, not just keywords. Just like your AI needs.

📋 Ecosystem Overview
# See your complete MCP ecosystem:

ncp list --depth 2

Get help anytime:

ncp --help

⚡ Direct Testing
# Test any tool safely:

ncp run filesystem read_file --path "/tmp/test.txt"

Why this matters: You can debug and test tools directly, just like your AI would use them.

✅ Verify Everything Works
# 1. Check NCP is installed correctly

ncp --version

2. Confirm your MCPs are imported

ncp list

3. Test tool discovery

ncp find "file"

4. Test a simple tool (if you have filesystem MCP)

ncp run filesystem read_file --path "/tmp/test.txt" --dry-run

✅ Success indicators:

  • NCP shows version number
  • ncp list shows your imported MCPs
  • ncp find returns relevant tools
  • Your AI client shows NCP's gateway tools; an Apps-capable host may also show selected app callback tools

💪 From Tools to Automation: The Real Power

You've seen find (discover tools) and code (execute TypeScript). Individually, they're useful. Together with scheduling, they become an automation powerhouse.

A Real Example: The MCP Conference Scraper

We wanted to stay on top of MCP-related conferences and workshops for an upcoming release. Instead of manually checking websites daily, we asked Claude:

"Set up a daily scraper that finds MCP conferences and saves them to a CSV file"

What Claude did:

  1. Used `code` to write the automation:
   // Search the web for MCP conferences

const results = await web.search({ query: "Model Context Protocol conference 2025" });

// Read each result and extract details for (const url of results) { const content = await web.read({ url }); // Extract title, deadline, description... // Save to ~/.ncp/mcp-conferences.csv }

  1. Used `schedule` to automate it:
   ncp schedule create code:run "every day at 9am" \

--name "MCP Conference Scraper" \ --catchup-missed

How to set this up yourself:

First, install the web photon (provides search and read capabilities):

# Install from the official photons repo

ncp photon add https://raw.githubusercontent.com/p

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx