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

ui-ticket-mcp

作者:0ics-srls版本 1.6.2i★ –i在你的电脑上运行
注册名称io.github.0ics-srls/ui-ticket-mcp

安装

概览

作者提供的说明(英文原文)

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

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: 开发者工具
  • 你需要填写:PROJECT_ROOT

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)。
  • 需要你自己填写: PROJECT_ROOT, REVIEW_PORT

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 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": {
    "ui-ticket": {
      "command": "uvx",
      "args": [
        "ui-ticket-mcp"
      ],
      "env": {
        "PROJECT_ROOT": "your-value",
        "REVIEW_PORT": "your-value"
      }
    }
  }
}

在终端中运行这条命令

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

运行前请先填写空着的值。

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

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

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。

需要你填写的值

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

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 0ics-srls 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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 4915 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4915 个服务器的 96% 更新
  • 基础检查结果等于或优于此分类中其他 4915 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

ui-ticket-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?

你需要填写:PROJECT_ROOT

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(1.6.2)于昨天进入注册中心。

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 Python (uv)。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

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

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

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

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
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。

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'

只显示了开头部分;其余内容请在仓库中阅读

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