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PopNx MCPMCP servers for people who use AI · explained in plain words

ui-ticket-mcp

by 0ics-srlsversion 1.6.2i★ –iRuns on your computer
Registry nameio.github.0ics-srls/ui-ticket-mcp

Install

Overview

Description from the maker (original English)

Human-to-AI code review bridge. Review UI in the browser, AI agents fix code via MCP.

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: Developer tools
  • You need to fill in: PROJECT_ROOT

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).
  • You fill in yourself: PROJECT_ROOT, REVIEW_PORT

You need

  • PyPIPython’s uv installed (for the uvx 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": {
    "ui-ticket": {
      "command": "uvx",
      "args": [
        "ui-ticket-mcp"
      ],
      "env": {
        "PROJECT_ROOT": "your-value",
        "REVIEW_PORT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ui-ticket --env PROJECT_ROOT=your-value --env REVIEW_PORT=your-value -- uvx ui-ticket-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "ui-ticket": {
      "command": "uvx",
      "args": [
        "ui-ticket-mcp"
      ],
      "env": {
        "PROJECT_ROOT": "your-value",
        "REVIEW_PORT": "your-value"
      }
    }
  }
}

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": {
    "ui-ticket": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ui-ticket-mcp"
      ],
      "env": {
        "PROJECT_ROOT": "your-value",
        "REVIEW_PORT": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • PROJECT_ROOT required env
    Root directory of the project being reviewed
  • REVIEW_PORT env
    HTTP port for REST API (default: 3200)

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account 0ics-srls, 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 Developer toolsi

  • More stars than 0% of the other 4912 servers in this category
  • Published to the registry more recently than 96% of the other 4912 servers in this category
  • Basic checks equal to or better than 100% of the other 4912 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 ui-ticket-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?

You need to fill in: PROJECT_ROOT

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 (1.6.2) reached the registry yesterday.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

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

GitHub

by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 4 days ago
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Desktop Commander

by wonderwhy-er

MCP server for terminal commands, file operations, and process management

Runs on your computer★ 10,225MITUpdated 16 days ago
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Cloudflare MCP

by cloudflare

Cloudflare MCP servers

Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
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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.

ui-ticket-mcp

Human-to-AI code review bridge. Review UI prototypes directly in the browser, then let AI agents read your feedback and fix the code automatically.

You click on elements, write review comments like "This button should be blue" or "The spacing is wrong here", and your AI coding agent (Claude Code, Codex, Cursor, etc.) picks them up via MCP and resolves them - with full context about which element you pointed at, its CSS, position, and surrounding DOM.

How it works

journey

title Using ui-ticket-mcp section Review Open your app in browser: 5: You Click on a broken element: 4: You Write what's wrong: 5: You section AI resolves Agent reads your feedback: 3: AI Agent finds the source file: 4: AI Agent fixes the code: 5: AI Review disappears: 5: You, AI

One Python process handles everything - MCP protocol for the agent (stdio) and REST API for the browser UI (HTTP). Reviews are stored in a SQLite database inside your project.


Quick Start

1. Connect to your AI agent

Add to your project's .mcp.json (Claude Code, Codex, Cursor, etc.):

{

"mcpServers": { "ui-ticket-mcp": { "command": "uvx", "args": ["ui-ticket-mcp"], "env": { "PROJECT_ROOT": "/path/to/your/project", "REVIEW_PORT": "3200" } } } }

Restart the agent. uvx downloads and runs the package automatically - no manual install needed.

Alternative: pip install ui-ticket-mcp, then use "command": "ui-ticket-mcp" instead of uvx.

When the MCP server starts, it also launches a REST API on http://localhost:3200 (or your custom REVIEW_PORT) for the browser UI.

Important: The API always runs locally (localhost). The website https://uiticket.0ics.ai/ is the landing page only — it is NOT an API endpoint. Always use http://localhost:{PORT}/api as the api-url.

2. Add the browser UI to your app
npm install ui-ticket-panel

In your app's entry file (e.g. main.ts, index.tsx):

import { defineReviewPanel } from 'ui-ticket-panel';

defineReviewPanel();

Then in your root template:

<review-panel api-url="http://localhost:3200/api"></review-panel>

That's it. Works in any framework - Angular, React, Vue, Svelte, or plain HTML. It's a standard Web Component. For SSR frameworks (Next.js, Nuxt, SvelteKit) see the Framework Examples section — you need a dynamic import on the client side.

No bundler? Use CDN
<script type="module" src="https://unpkg.com/ui-ticket-panel/dist/bundle.js"></script>

The bundle auto-registers the element. No npm install, no build step needed.

3. Start reviewing

Open your app in the browser. You'll see a floating chat button in the bottom-right corner. Click it to open the review panel, or press Alt+A to enter annotation mode and click directly on elements.


Browser UI Features

Review Panel

The floating panel lets you browse, filter, and manage all reviews:

  • Filter tabs - Switch between Open, Resolved, and All reviews
  • Search - Full-text search across all review comments
  • Tag filter - Filter by category: general, bug, suggestion, question
  • Per-review actions - Resolve, Reopen, Delete, Reply, Highlight element
  • Threaded replies - Reply to reviews for back-and-forth discussion
  • Manual review form - Write reviews without annotation (Ctrl+Enter to submit)
  • Badge counter - Floating button shows count of open reviews
Annotation System

The annotation system lets you point at specific elements and attach reviews to them:

  • Click-to-annotate - Press Alt+A (or the target button), then click any element
  • Multi-select drag - Click and drag to select a region of multiple elements
  • Hover preview - See element identification in real-time as you move the mouse
  • Smart popup - Appears above or below the element depending on available space

When you annotate an element, the system captures rich metadata that helps the AI agent understand exactly what you're pointing at:

Captured dataExample
Element nameButton 'Save', Input[email] 'Your email', Heading 2 'Features'
CSS selector#main-header, div.card > button.primary:nth-of-type(2)
Bounding boxPosition and dimensions in pixels
Nearby textOwn text + previous/next sibling text for context
Selected textIf you highlight text before annotating
CSS classesFiltered (excludes framework-generated hashes)
Computed stylesColor, background, font, border, padding (smart per element type)
Full DOM pathbody > div#app > section.content > div.card > button
AccessibilityARIA roles, labels, tabindex, focusability
Sibling contextParent tag, children count, adjacent sibling tags
Marker Badges

Reviews with annotations show numbered badges on the page next to the annotated element:

  • Single review - Circular badge with the review ID, colored red (open) or green (resolved)
  • Stacked reviews (3+ on the same element) - Pill badge showing count, with a gradient showing open/resolved ratio
  • Click badge - Opens the review in the panel
  • Delete badge - Remove via the X button on hover
  • Tooltip - Hover to see author, element name, and comment preview
Tags

Every review can be tagged with a category:

TagColorUse for
generalIndigoGeneral feedback (default)
bugRedSomething is broken
suggestionGreenImprovement idea
questionAmberNeeds clarification
Keyboard Shortcuts
ShortcutAction
Alt+AToggle annotation mode
Ctrl+EnterSubmit review or reply
EscapeClose popup / exit annotation mode

Architecture

graph LR

Agent[AI Agent] Browser[Reviewer - Browser] Server[ui-ticket-mcp] DB[(SQLite)]

Agent <-->|stdio MCP| Server Browser <-->|HTTP REST :3200| Server Server --- DB

  • MCP (stdio) - Your agent framework starts it automatically. 10 tools for AI agents to read, resolve, and manage reviews.
  • REST API (HTTP :3200) - Starts in background, serves the browser review UI. CORS enabled for all origins.
  • SQLite (WAL mode) - Concurrent readers + 1 writer, 5s busy timeout. Database lives inside your project at .reviews/reviews.db.

MCP Tools

10 tools available to AI agents:

get_review_summary()

Overview of all pages with review counts.

Page         | Open | Resolved | Total

------------ | ---- | -------- | ----- user-profile | 3 | 1 | 4 dashboard | 0 | 2 | 2

get_reviews(page_id?: str)

List review comments. Optionally filtered by page. Shows status, tag, element context, and reply chains.

[#1] [OPEN] [bug] user-profile - alice: The header spacing is off

→ Element: Heading 2 'User Profile' | Selector: h2.page-title [#2] [RESOLVED] user-profile - bob: Button color should be blue

get_annotated_reviews(page_id?: str)

Returns only reviews that have element annotation metadata. Includes element name, CSS selector, full DOM path, selected text, accessibility info - everything the agent needs to locate and understand the annotated element.

get_pending_work()

All open reviews grouped by page - the agent's "todo list".

## user-profile (2 open)
  • #1 [bug] (alice): The header spacing is off
  • #3 [suggestion] (alice): Add hover state to buttons

dashboard (1 open)

  • #4 (bob): Chart labels are truncated
add_review(page_id, author, text, tag?, metadata?, parent_id?)

Create a new review. Supports tags, annotation metadata (JSON), and threading via parent_id.

resolve_review(review_id, resolved_by?)

Mark a review as resolved. Sets resolved_at timestamp and resolved_by (defaults to "agent").

reopen_review(review_id)

Reopen a previously resolved review. Clears resolution info.

batch_resolve(page_id, resolved_by?)

Resolve all open reviews on a page at once. Returns Resolved 3 review(s) on user-profile.

find_source_file_tool(page_id)

Find source files in PROJECT_ROOT matching a page ID. Searches by kebab-case, CamelCase, and glob patterns. Skips node_modules, dist, .git.

Found 3 file(s) for 'user-profile':
  • src/app/user-profile/user-profile.component.ts
  • src/app/user-profile/user-profile.component.html
  • src/app/shared/UserProfile.ts
get_setup_guide()

Returns the full setup guide (MCP config, REST API, browser UI). Useful when the agent needs to help set up the review system in a new project.

Typical agent workflow
graph TD

A["get_pending_work()"] -->|See what needs attention| B["get_annotated_reviews(page)"] B -->|Get element metadata for context| C["find_source_file_tool(page)"] C -->|Locate the source files| D["Read & edit the code"] D --> E{Resolve} E -->|Single| F["resolve_review(id)"] E -->|All on page| G["batch_resolve(page)"]


REST API

All endpoints under /api. CORS enabled for all origins.

Reviews
MethodEndpointDescription
GET/api/reviews/summaryPer-page summary with open/resolved counts
GET/api/reviewsAll reviews (newest first)
GET/api/reviews/{page_id}Reviews for a page. Query: `?status=open\resolved, ?tag=bug\suggestion\...`
POST/api/reviews/{page_id}Create review
PATCH/api/review/{id}Update review (status, text, tag, metadata)
DELETE/api/review/{id}Delete review permanently
Replies
MethodEndpointDescription
GET/api/review/{id}/repliesGet all replies to a review (chronological)
POST/api/reviews/{page_id}Create reply (include parent_id in body)
POST body
FieldTypeDefaultDescription
textstring-Review comment (required)
authorstring"anonymous"Reviewer name
tagstring"general""general", "bug", "suggestion", or "question"
metadataobject-Annotation context (element, selector, styles, etc.)
parent_idinteger-Parent review ID for threaded replies
PATCH body
FieldTypeDescription
status"open" \"resolved"Resolving auto-sets resolved_at and resolved_by
textstringUpdated comment text
tagstringUpdated tag
resolved_bystringWho resolved it (default: "user" via API, "agent" via MCP)
metadataobjectUpdated annotation metadata

Database

Reviews are stored in SQLite inside your project at {PROJECT_ROOT}/.reviews/reviews.db. The database is auto-created on first run.

The .reviews/ directory includes:

FilePurpose
reviews.dbSQLite database (commit to git to share reviews with your team)
.gitkeepEnsures directory is tracked
.gitignoreIgnores WAL temp files (*.db-wal, *.db-shm)

Path resolution:

  1. REVIEW_DB_PATH env var (explicit override)
  2. PROJECT_ROOT/.reviews/reviews.db (default)
  3. ./reviews.db (fallback)
Schema
reviews (

id INTEGER PRIMARY KEY, page_id TEXT NOT NULL, author TEXT DEFAULT 'anonymous', text TEXT NOT NULL, status TEXT DEFAULT 'open', -- 'open' | 'resolved' created_at TEXT NOT NULL, -- ISO 8601 resolved_at TEXT, resolved_by TEXT, metadata TEXT, -- JSON: annotation context tag TEXT DEFAULT 'general', -- 'general' | 'bug'

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