yo-bug
An MCP server that gives AI coding assistants QA superpowers, enabling users to report bugs by pointing, clicking, or typing while automatically capturing diagnostic data for AI-driven test-feedback-fix loops.
README
yo-bug 🐛
English · 简体中文
"Yo, bug!" — Point at bugs, AI fixes them.

MCP Server that gives AI coding assistants QA superpowers. One install, then your AI handles the entire test-feedback-fix loop.
In vibe coding, the bottleneck is testing: humans find bugs but struggle to describe them. yo-bug solves this by letting users point, click, or type — while the AI automatically receives element locations, console errors, network failures, action recordings, and annotated screenshots.
What it does
| For the Human | For the AI |
|---|---|
| Click a broken element → done | Gets: CSS selector + computed styles + React/Vue component name |
| Draw on a screenshot → done | Gets: annotated PNG as inline image content |
| Type a behavior bug ("scroll doesn't auto-jump") → done | Gets: structured text feedback linked to a checklist case |
| Check off a multi-step test case | Gets: which cases passed/failed, with linked feedback per case |
| Just use the app normally | Gets: last 100 user actions + 50 console errors + failed network calls |
The AI drives the entire workflow through MCP tools. Humans never need to learn commands, configure proxies, or modify their code.
Install
npx yo-bug install
(or npm install -g yo-bug && yo-bug install if you prefer a global install)
This auto-detects your AI tool (Claude Code / Cursor / Windsurf) and writes the MCP config. One time, done forever.
How it works
AI writes code
→ AI calls start_test_session()
→ Reverse proxy starts, injects test SDK into HTML responses
→ Browser opens (zero code changes to your project)
→ AI pushes grouped test cases (8 QA dimensions, multi-step scenarios)
→ Human runs each case; pass/fail at the case level
→ When failing, picks feedback mode: element / screenshot / text
→ AI calls list_feedbacks() + get_feedback() — sees diagnostic data
→ AI must state root cause BEFORE writing fix (enforced by tool response)
→ AI fixes → calls resolve_feedback() → browser shows verify card
→ Human clicks Fixed / Locate (jump to element) / Still broken
→ Loop until done
MCP Tools (9 total)
Session Control
| Tool | Description |
|---|---|
start_test_session(port?, open?, storage?) |
Start test mode: auto-detect dev server, launch reverse proxy with SDK injection, open browser. storage defaults to "project" (saves under <cwd>/.yo-bug/feedback/); pass "home" for ~/.yo-bug/ |
stop_test_session() |
Stop test mode, return session summary (feedback stats, checklist results, weak dimensions, whether dev server was auto-closed) |
Feedback
| Tool | Description |
|---|---|
list_feedbacks(status?, type?, limit?, all_sessions?) |
List submitted feedback. Defaults to current session only |
get_feedback(id) |
Full details: element info, console errors, network errors, action steps, annotated screenshot. Response includes a mandatory diagnostic protocol that forces the AI to identify root cause before writing code |
resolve_feedback(id) |
Mark as fixed → pushes a rich verification card to the browser (with screenshot thumbnail, element selector, page URL, locate button). Human confirms |
Test Checklist (Grouped Test Cases)
| Tool | Description |
|---|---|
create_checklist(title, cases) |
Push structured test cases to browser. Each case has a title, sequential steps[], expected result, priority, and QA dimension |
get_checklist_status() |
See which cases passed/failed and any user feedback per case |
Test History
| Tool | Description |
|---|---|
save_test_record(module, ...) |
Save test results per module. Accumulates history for future reference |
get_test_history(module) |
Get historical test records. Shows frequently failing scenarios so AI prioritizes coverage |
8 QA Test Dimensions
The create_checklist tool embeds professional QA methodology. AI is guided to cover:
- Happy path — Core functionality works end-to-end
- Empty/boundary — Empty inputs, special chars, max length, zero/negative values
- Error states — Offline, server errors, timeouts, recovery
- Duplicate ops — Double-click, re-submit, concurrent requests
- State recovery — Refresh, back/forward, deep links, tab close/reopen
- Loading/async — Loading states, failed loads, stale data
- Responsive — 375px mobile width, touch targets, overflow
- Interaction detail — Tab order, Enter/Escape, disabled states, focus
Each case is multi-step (open page → fill form → click submit → verify result), so the human marks a whole scenario passed/failed rather than micro-managing each step.
Three Feedback Modes
When a checklist case fails, users pick a mode that fits the bug:
| Mode | Shortcut | When to use |
|---|---|---|
| Element | Alt+E |
Visual / component bug — click the broken element, AI gets selector + styles + framework component name |
| Screenshot | Alt+S |
Layout / styling bug — drag to select a region, annotate with arrow / rect / circle / freehand / text |
| Text | (Checklist ✗) |
Behavior / logic bug ("doesn't auto-scroll", "wrong order") — pure description, AI uses console/network data to find cause |
Other shortcuts: Alt+X toggle mode bar, Esc exit anything.
In-Browser Feedback Management
Above the floating bug button you'll see a list icon with a red badge showing open feedback count. Click it to:
- See all open feedback you've submitted this session
- Edit description inline (click description text)
- Delete a feedback (trash icon, confirms first)
- View screenshot thumbnails
When all feedback is resolved, the button auto-hides.
Auto-Captured Context
Every feedback submission automatically includes:
- Console errors — last 50
console.error/console.warnentries with stack traces - Network failures — last 50 failed
fetch/XHRrequests with status, URL, duration - Unhandled exceptions — last 50
window.onerror+unhandledrejectionevents - Action recording — last 100 user actions (click / input / navigate / scroll / keypress) with timestamps
- Element info — CSS selector, tag, text content, bounding rect, computed styles, React/Vue component name (when in element mode)
Verify-Fix Flow
When AI calls resolve_feedback(), a rich verify card appears on the left:
┌─────────────────────────────┐
│ ▼ VERIFY FIX [3] │ ← collapsible header with count
├─────────────────────────────┤
│ [thumbnail*] "Button click │
│ does nothing" │
│ bug · element │
│ 📍 <button> #submit-btn │ ← only when element info exists
│ 🔗 /orders │
│ ⏱ 5 min ago │
│ [🎯 Locate*] [✓] [✗] │
└─────────────────────────────┘
* thumbnail only if a screenshot was attached
* Locate only if an element selector was captured
- 🎯 Locate scrolls to the element + flashes a red pulse twice. If the verify card was submitted on a different URL, it navigates there first. If the element no longer exists on the current page, shows a toast
- ✓ Fixed confirms the fix → status: resolved
- ✗ Still broken sends it back → status: open (AI sees it in next
list_feedbackscall) - Click the header bar to collapse the whole stack when it gets in the way
Theming
- Auto-detects
prefers-color-scheme(light or dark) - All UI uses design tokens, contrast-verified (WCAG AA)
- Glass-morphism panels with backdrop blur; clearly distinct from white host pages
Works Inside Modal Dialogs
If your app opens a <dialog>.showModal() (which traps focus and inerts the rest of the page), yo-bug still works: it detects the open modal via the :modal selector plus a MutationObserver, and relocates the SDK host inside the dialog so focus is shared.
This means you can submit text feedback even when a modal is open — the textarea will accept input normally. When the dialog closes, the host moves back out.
i18n
SDK auto-detects <html lang="...">:
- Any value starting with
zh(zh,zh-CN,zh-Hans, ...) → Chinese interface - Everything else → English interface
MCP tool descriptions are in English (AI translates to the user's language naturally in chat).
Architecture
Browser → Reverse Proxy (localhost:3695+) → Dev Server (localhost:5173)
│
├─ Auto-injects SDK into HTML responses
├─ WebSocket passthrough (HMR works normally)
├─ Feedback API (POST/GET/PATCH/DELETE)
├─ Checklist API (push/poll/update)
└─ Verify API (push/confirm)
MCP Server (stdio) ← AI Tool (Claude Code / Cursor / Windsurf)
│
├─ start/stop_test_session → controls proxy lifecycle
├─ feedback tools → reads user submissions w/ diagnostic protocol
├─ checklist tools → pushes grouped test cases, reads results
└─ history tools → persists test records per module
The proxy auto-detects dev server framework (Vite, Next.js, CRA, Webpack, Nuxt, Angular, Svelte, Astro) and port. If the dev server is already running, it connects. If not, it starts one. On stop_test_session it cleans up — and tells the AI whether the dev server was auto-closed or left running (because the user had started it themselves).
If port 3695 is taken, yo-bug auto-increments to 3696, 3697... up to 3795. Multiple projects can run yo-bug simultaneously without conflict.
Security
- All data stays local — feedback files in
<project>/.yo-bug/feedback/by default (auto-.gitignore'd), or~/.yo-bug/if you opt in - Feedback IDs validated against path traversal
- Input fields whitelist-filtered and length-limited
- Network interceptor uses exact pathname matching (no substring false positives)
- No data sent to any external service
Requirements
- Node.js >= 18
- Any MCP-compatible AI tool
- A current-version browser (Chrome / Edge / Firefox / Safari)
License
MIT
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