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Tracebug

by prashantsinghmangatversion 1.11.5i★ –iRuns on your computer
Registry nameio.github.prashantsinghmangat/tracebug

Install

Overview

Description from the maker (original English)

AI agents read TraceBug bug reports (console, network, replay, repro timeline) from local disk.

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": {
    "tracebug": {
      "command": "npx",
      "args": [
        "-y",
        "tracebug",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add tracebug -- npx -y tracebug mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "tracebug": {
      "command": "npx",
      "args": [
        "-y",
        "tracebug",
        "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": {
    "tracebug": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "tracebug",
        "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 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account prashantsinghmangat, 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 32497 servers in this category
  • Published to the registry more recently than 86% of the other 32497 servers in this category
  • Basic checks equal to or better than 100% of the other 32497 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 Tracebug 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 (1.11.5) reached the registry 5 days 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, Zoo MCP

Alternatives

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

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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Zoo MCP

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An MCP server that provides access to the Zoo API for various CAD operations and tools.

Runs on your computerUpdated today
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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.

TraceBug

Capture the bug. Let AI fix it.

Local-first, zero backend. One .html file — full replay, console errors, network requests, repro timeline — that your AI coding agent reads over MCP and fixes. Opens offline for humans too.

▶ Watch the 1-minute demo ( vertical Short ) · watch Claude debug a real bug · try it live in the sandbox


TraceBug is a local-first debugging assistant. Capture a bug → produce a single self-contained .html file → hand it to your AI coding agent (Claude Code, Cursor, Windsurf), which reads the evidence over a local MCP server and fixes it — or email/Slack it to a human dev who opens it offline. Every report also embeds a failing test the agent runs to verify the fix.

Every report opens with:

🔍 Possible Cause (high confidence): API POST /orders failed with 500 after clicking 'Place Order'

TL;DR: TypeError thrown on /checkout when clicking 'Place Order' button

No accounts. No SaaS lock-in. Data stays in your browser by default.

Optional cloud sharing (built, UI-gated off by default): if you'd rather share a URL than a file, sign in once and get a share link with the same content. The code ships behind a feature flag (PHASE2-CLOUD); the Share button stays disabled until the portal is switched on. Local .html export is the supported sharing path today.

Works with any frontend framework: React, Angular, Vue, Next.js, Nuxt, Vite, Svelte, SvelteKit, Remix, Astro, or plain HTML.

⚡ Get Started in 30 Seconds

New here? [Report your first bug in 2 minutes →](docs/quickstart.md)

npx tracebug init

That's it. The CLI detects your framework and prints the exact 2-line snippet. Paste it into your app, run npm run dev, and you'll see the TraceBug toolbar on the right edge.

Report a bug in 2 clicks:

  1. Press `Ctrl+Shift+B` (or click the ⚡ button on the toolbar)
  2. Review the auto-filled report, click "Copy GitHub Issue"
  3. Paste into your repo. Done.

What TraceBug Does

Tester opens the page

↓ Arm a session (idle until you act): • ⚡ Quick Bug — Ctrl+Shift+B opens the ticket-review modal • 📷 Screenshot / Region • 🔴 Record — Sentry mode: rolling video buffer + HUD with timestamped comments. File multiple bugs from one screen-share. • ⏺ Track session — event-only capture (no video). Survives full-page navigation, so clicking a link keeps recording. ↓ The SDK captures: clicks, inputs, navigation, API calls, console, errors, the DOM stream (rrweb), environment, and a redacted Web-Storage snapshot ↓ Review the ticket, then export: • Export .html — self-contained interactive DOM replay (KB, not MB) • Export for AI (.html) — tiny text-only report to paste into a chat • Download report (.md) · .zip (GitHub-attachable) · failing test (.spec.ts) • Export HAR · file a real GitHub/Linear/Slack/Jira issue ↓ Complete report includes:

  • Auto-generated title + smart summary + root-cause hint (high/medium/low confidence)
  • Steps to reproduce, full session timeline
  • Interactive DOM replay (or screen recording .webm), screenshots
  • Console errors + stack traces, failed network requests with response snippets
  • Environment (browser, OS, viewport, device) ↓

Send the .html → developer opens it offline and sees exactly what happened, or an MCP-connected coding agent reads it and debugs from it.

Scan Page (a11y via axe-core, broken images, mixed content, frustration

signals, failed/slow APIs, JS errors) is available programmatically as

TraceBug.scanPage(); it is no longer a toolbar button.

Two Ways to Use TraceBug

Option 1: npm Package (For Developers)

Install the SDK in your project — best for teams who want TraceBug always active on dev/staging.

npm install tracebug-sdk
import TraceBug from "tracebug-sdk";

TraceBug.init({ projectId: "my-app" });

Option 2: Chrome Extension (For Non-Developers)

Install the browser extension — no code needed. QA testers, PMs, and clients can use it on any website.

[Install from Chrome Web Store](https://chromewebstore.google.com/detail/fdemmibikigigkfjngclmdheeajhdgaj) — one click, works immediately.

BrowserSupported
ChromeYes — install from Chrome Web Store
EdgeYes — Chrome Web Store extensions work natively
BraveYes — Chrome Web Store extensions work natively
OperaYes — install "Install Chrome Extensions" add-on first
FirefoxYes — install from Firefox Add-ons (Firefox 128+)

Browser support

Browsernpm SDKExtension
Chrome✅✅
Edge✅✅
Brave / Opera✅✅
Firefox✅✅ (128+)
Safari✅¹❌ (SDK only)

The SDK is framework- and browser-agnostic — it runs anywhere modern JS runs. ¹ The interactive DOM-replay export uses the browser-native CompressionStream / DecompressionStream (Chrome 80+, Firefox 113+, Safari 16.4+); on older engines the exporter ships the replay uncompressed and the viewer falls back to the screenshot gallery. The extension runs on Chromium browsers and Firefox 128+ (no Safari build — on Safari, use the npm SDK).

Features

🧠 Debugging Assistant (v1.3)

Every report opens with four derived signals that turn "what happened" into "why it likely happened":

SignalWhat it looks like
🔍 Root Cause Hint"API POST /orders failed with 500 after clicking 'Place Order'" with confidence tier (high/medium/low)
TL;DROne-sentence summary combining network + error + click + page signals
User clickedTag, text, selector, id, aria-label, testId for the last click before the bug
Recent ActionsLast ~10 user actions as plain-English steps ("Clicked 'Edit' button", "Navigated to /checkout")

Plus:

  • Network response snippets — first 200 chars of every failed fetch/XHR response body, captured asynchronously (never blocks the request)
  • In-memory failure buffer — last 10 failed requests accessible via TraceBug.getNetworkFailures()
  • Deterministic — pure functions, no AI APIs, O(1) on already-computed report fields

All four signals ship inline in GitHub issues, Jira tickets, PDF reports, and the Quick Bug modal. See docs/bug-reporting.md for full output examples.

🤖 MCP Server — AI Agents Debug Your Reports (v1.5)

Your coding agent (Claude Code, Cursor, Windsurf, VS Code) reads TraceBug bug reports and fixes the bug — fully local, nothing uploaded:

claude mcp add tracebug -- npx -y tracebug mcp --dir ./bug-reports

-y skips npx's install prompt but does not pin a version — it resolves whatever's newest on the npm registry at the time it runs. For a known, audited build instead, pin explicitly: npx tracebug@1.10.1 mcp --dir ./bug-reports (bump the version when you deliberately upgrade).

The server reads the same self-contained .html files TraceBug exports. A tester hands a dev the report file, the dev drops it in the repo, and the agent gets nine tools: list_bug_reports, get_bug_report, get_console_errors, get_network_activity, get_repro_steps, get_screenshot (real image content), get_playwright_test, resolve_stack, and get_fix_context. get_bug_report returns a prioritized investigation guide computed from what the report contains, so the agent knows exactly which tools to call next. Console stacks + failed-request bodies + repro steps + frustration signals — everything an agent needs to go from bug report to fix.

The last three close the fix loop (v1.9): get_playwright_test returns the generated failing Playwright spec that replays the session and asserts the captured failure is gone — red until the bug is fixed, green after — so the agent can run it, patch, and re-run until green. resolve_stack maps the report's minified stack frames to original source files/lines using .map files found in the repo the server runs from. get_fix_context is a one-call fix starter: the failing request with response snippet, the user action that triggered it, the source-map-resolved top stack frames, and whether a failing test is available.

Kicking off is one paste: the extension shows a ready-made agent prompt after every Export .html (auto-copied), the exported file itself carries the same prompt in its AI tab, and in Claude Code you can just type /tracebug:debug_bug_report.

Other tools' MCP servers are cloud-hosted: your bug data must live on their servers first. TraceBug's runs on your machine over stdio and opens zero network connections. Try it instantly — this repo ships a demo report and a pre-configured .mcp.json. See docs/mcp.md.

🎭 Playwright Reporter — Bug Reports From Failed Tests (v1.6)

Every failed Playwright test becomes the same self-contained .html bug report — assertion error + code snippet, step timeline as repro steps, page console + network (via the optional fixture), failure screenshot, and a root-cause hint. Upload bug-reports/ as a CI artifact, then debug it with your agent via the MCP server:

// playwright.config.ts — that's the whole setup

reporter: [["list"], ["tracebug-sdk/playwright", { outputDir: "bug-reports" }]],

Nobody else captures bugs from test runs as portable files — cloud tools can't attach their viewer to a CI artifact. See docs/playwright.md.

🧠 AI Debugger — BYO-Key LLM Analysis (v1.6)

Run real LLM root-cause analysis with your own key — Anthropic, OpenAI, or local Ollama. The call goes directly from your browser to the provider: TraceBug never sees the key, the prompt, or the response, and the prompt is scrubbed of secret shapes before it leaves the page. No metered credits, no vendor cloud in the path.

Combined with the local heuristic hint and the local MCP server, this is AI debugging that never phones home — the one position no cloud-hosted, metered competitor can copy.

Only the beginning is shown; read the rest in the repo

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