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Perfonext Render MCP

by souvikduversion 0.5.2i★ –iRuns on your computer
Registry nameio.github.souvikdu/perfonext-render-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account souvikdu, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32568 servers in this category
  • Published to the registry more recently than 33% of the other 32568 servers in this category
  • Basic checks equal to or better than 100% of the other 32568 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Perfonext Render MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.5.2) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FlyDocs

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

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

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

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

Runs in the cloud★ 211Updated yesterday
Install

FlyDocs

by flydocs.ai

Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.

Runs on your computerUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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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