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

Perfonext Render MCP

作者:souvikdu版本 0.5.2i★ –i在你的电脑上运行
注册名称io.github.souvikdu/perfonext-render-mcp

安装

概览

作者提供的说明(英文原文)

MCP server for analyzing React Profiler exports: rerenders, commit spikes, slow components.

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)。
  • 注册中心没有列出需要填写的密钥。

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": {
    "perfonext-render": {
      "command": "npx",
      "args": [
        "-y",
        "@perfonext/render-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add perfonext-render -- npx -y @perfonext/render-mcp

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": {
    "perfonext-render": {
      "command": "npx",
      "args": [
        "-y",
        "@perfonext/render-mcp"
      ]
    }
  }
}

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": {
    "perfonext-render": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@perfonext/render-mcp"
      ]
    }
  }
}

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。

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 souvikdu 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 32583 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32583 个服务器的 33% 更新
  • 基础检查结果等于或优于此分类中其他 32583 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

Perfonext Render MCP 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(0.5.2)于2个月前进入注册中心。

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, sync. labs

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
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sync. labs

作者:synchronicity-labs

Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.

电脑或云端今天更新
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。

perfonext-render-mcp

Analyze React render behavior in Next.js apps and apply fixes in the editor.

perfonext-render-mcp is a Model Context Protocol (MCP) server that gives GitHub Copilot, Claude Desktop, Claude Code, and other MCP clients structured, machine-readable React render analysis for Next.js performance work. It turns live capture sessions and React DevTools Profiler exports into component costs, exact rerender causes, and regression diffs — evidence an MCP client can act on directly.

Quick Start

perfonext-render-mcp is a standard MCP stdio server, so it works with any MCP-compatible client (GitHub Copilot in VS Code, Claude Desktop, Claude Code, Cursor, and others). Run it directly with npx:

npx -y @perfonext/render-mcp

Or install globally:

npm install -g @perfonext/render-mcp

The executable command remains perfonext-render-mcp after installation.

VS Code

Add the server to .vscode/mcp.json (the workspace MCP configuration file):

{

"servers": { "perfonext-render": { "type": "stdio", "command": "npx", "args": ["-y", "@perfonext/render-mcp"] } } }

Reload the VS Code window and run MCP: List Servers to start it, or accept the trust prompt when it appears.

Claude Desktop

Add the server to claude_desktop_config.json:

{

"mcpServers": { "perfonext-render": { "command": "npx", "args": ["-y", "@perfonext/render-mcp"] } } }

Restart Claude Desktop to pick up the new server.

Claude Code

Add the server with the CLI:

claude mcp add perfonext-render -- npx -y @perfonext/render-mcp

Or add the same mcpServers entry to .mcp.json.

Other MCP clients

Any client that supports stdio MCP servers can launch npx -y @perfonext/render-mcp. Consult your client's documentation for its MCP server configuration format.

For a locally-built checkout, point command/args at node and the repo's dist/index.js instead.

Troubleshooting

spawn npx ENOENT / spawn node ENOENT on macOS with nvm

If the server fails to start with this error, your GUI MCP client likely cannot see nvm. GUI apps on macOS do not load shell config (.zshrc/.bashrc), so nvm-installed npx/node are not on PATH. Use an absolute npx path and include the same Node directory in PATH:

{

"servers": { "perfonext-render": { "type": "stdio", "command": "/Users/YOU/.nvm/versions/node/v /bin/npx", "args": ["-y", "@perfonext/render-mcp"], "env": { "PATH": "/Users/YOU/.nvm/versions/node/v /bin:/usr/bin:/bin" } } } }

Merge these fields into your client's server entry, under servers for VS Code or mcpServers for Claude Desktop/Code. Then ask your assistant: _"Run a render analysis on my app."_

What It Does

perfonext-render-mcp is the agent companion to React DevTools Profiler and react-scan — best at machine-readable summaries, exact rerender-cause attribution, source-aware follow-up, and diffing. The loop is collect → analyze → fix, all locally:

  • collect — choose live capture (react-scan/lite streams events in real time) or manual DevTools export
  • analyze — the MCP returns structured, machine-readable evidence: component costs, rerender causes, commit breakdowns, and regressions
  • fix — your MCP client uses that evidence to propose and apply concrete code changes

Note: while a live capture session is active, React DevTools Timeline Profiler will not receive events

(react-scan/lite takes over the profiling channel). Calling stop_render_capture restores it.

Capabilities:

  • live capture — streams per-commit fiber events from a running React app directly into the MCP over a local HTTP endpoint; no manual export required
  • manual export — loads exported React DevTools Profiler JSON files as an alternative input path
  • summarizes commits, the most expensive components, and detected render issues in one call
  • ranks the hottest commits and shows the top components inside each spike
  • identifies the slowest components by total render cost
  • highlights components with repeated rerenders, reporting the exact changed props/state/hooks when live capture provides changeDescription data, and falling back to deterministic heuristics otherwise
  • annotates ranked components with their source file and line when available
  • filters DOM host elements (div, span, …) and unnamed components out of ranked output so findings stay actionable
  • compares two render profiles to surface regressions and improvements
  • keeps profiles in memory so an MCP client can iterate without re-loading

Tools

Entry point
ToolDescription
begin_render_analysisEntry point. Accepts `approach: "live" \"manual". For live: starts a capture session and returns the instrumentation snippet. For manual`: returns React DevTools Profiler export steps.
Live capture
ToolDescription
run_render_captureCalled after instrumentation is wired up. Accepts `method: "manual-interaction" \"test-suite"`. Returns focused instructions for whichever method the user picks.
stop_render_captureStop the session, finalize buffered events into a profile, and return a profileId plus dataQuality (exact \heuristic) for analysis
get_captured_rendersOptional diagnostic: peek at session progress without stopping (commit count, unknown events). Only call if something seems wrong.
Analysis
ToolDescription
load_render_profileParse and load an exported React DevTools Profiler JSON file from disk (manual path entry point)
get_render_summarySummarize a loaded profile: top components by render cost, hottest commits, and detected render issues
get_hot_commitsRank the most expensive commits and show the top components inside each spike
get_slow_componentsRank the slowest components by total actual render time
get_rerender_causesExplain rerender causes with evidence, confidence, and a risk score. Reports exact changed props/state/hooks when changeDescription data is present (dataQuality: "exact"), heuristics otherwise
compare_rendersDiff two loaded render profiles and rank regressions, improvements, additions, and removals

Usage Walkthrough

Ask your assistant: _"Run a render analysis on my app."_

Your MCP client calls begin_render_analysis and asks you to choose:

Option A — Live capture (recommended)

Your MCP client will:

  1. Start a capture session (ingest server on 127.0.0.1:7721)
  2. Install react-scan as a devDependency if not present
  3. Write instrumentation-client.js at your project root with the session snippet
  4. Import it from your app's client-side entry point
  5. Ask whether you want to interact manually or run a test suite (run_render_capture)
  6. Stop the session and run analysis

Running a test suite? Use npx playwright test as usual. react-scan/lite installs

__REACT_DEVTOOLS_GLOBAL_HOOK__ itself, so a visible window and the React DevTools extension are not

required. The run still yields changeDescription data and dataQuality: "exact".

Two preconditions commonly cause a silent `commitCount: 0`:

- Build flavor. A plain next build/next start compiles out React's profiling hooks entirely.

Choose one of:

- next dev — real component names, but dev-mode overhead means render timings and proportions

may not match what real users experience in production.

- next build --profile then next start — production-accurate timings, but component names get

minified to 1-2 letters (e.g. "V") by production minification, regardless of the profiling flag.

get_render_summary surfaces a warning when this is detected.

- Instrumentation timing. instrument() must run before React initializes — a static top-level import

(as shown in the generated snippet) works; mounting it as a React component, or calling it inside a

useEffect, runs too late and silently captures nothing.

The ingest server runs on a fixed port (7721). Only the sessionId line in instrumentation-client.js changes between sessions — the file does not need to be re-wired each time.

Option B — Manual DevTools export

  1. Open React DevTools in the browser → Profiler tab → Record
  2. Interact with the app
  3. Export the JSON and share the file path
  4. Your MCP client calls load_render_profile({ filePath: "..." })

Example Prompts

  • "Run a render analysis on my app."
  • "Stop the capture and show me the slowest components."
  • "Which components are re-rendering the most and why?"
  • "Compare this run to the profile I captured before the refactor."
  • "I already have a React DevTools export — load it and tell me what's slow."
  • "Show me the hottest commits and which components dominated each spike."

Related Perfonext Tools

Development

npm install

npm run build npm test

Sample fixtures live under tests/fixtures/.

License

MIT

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