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.
Description from the maker (original English)
Human-to-AI code review bridge. Review UI in the browser, AI agents fix code via MCP.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
PROJECT_ROOT, REVIEW_PORTYou need
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-mcpFill in the empty values before running it.
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.
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.
REVIEW_PORT envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account 0ics-srls, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
You need to fill in: PROJECT_ROOT
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).
The GitHub repo last changed –, and the latest version (1.6.2) reached the registry yesterday.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
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’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.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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.
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.
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.
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 ofuvx.
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 websitehttps://uiticket.0ics.ai/is the landing page only — it is NOT an API endpoint. Always usehttp://localhost:{PORT}/apias theapi-url.
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.
<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.
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.
The floating panel lets you browse, filter, and manage all reviews:
The annotation system lets you point at specific elements and attach reviews to them:
When you annotate an element, the system captures rich metadata that helps the AI agent understand exactly what you're pointing at:
| Captured data | Example |
|---|---|
| Element name | Button 'Save', Input[email] 'Your email', Heading 2 'Features' |
| CSS selector | #main-header, div.card > button.primary:nth-of-type(2) |
| Bounding box | Position and dimensions in pixels |
| Nearby text | Own text + previous/next sibling text for context |
| Selected text | If you highlight text before annotating |
| CSS classes | Filtered (excludes framework-generated hashes) |
| Computed styles | Color, background, font, border, padding (smart per element type) |
| Full DOM path | body > div#app > section.content > div.card > button |
| Accessibility | ARIA roles, labels, tabindex, focusability |
| Sibling context | Parent tag, children count, adjacent sibling tags |
Reviews with annotations show numbered badges on the page next to the annotated element:
Every review can be tagged with a category:
| Tag | Color | Use for |
|---|---|---|
general | Indigo | General feedback (default) |
bug | Red | Something is broken |
suggestion | Green | Improvement idea |
question | Amber | Needs clarification |
| Shortcut | Action |
|---|---|
| Alt+A | Toggle annotation mode |
| Ctrl+Enter | Submit review or reply |
| Escape | Close popup / exit annotation mode |
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
.reviews/reviews.db.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)
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':
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.
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)"]
All endpoints under /api. CORS enabled for all origins.
| Method | Endpoint | Description | |||
|---|---|---|---|---|---|
| GET | /api/reviews/summary | Per-page summary with open/resolved counts | |||
| GET | /api/reviews | All 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 |
| Method | Endpoint | Description |
|---|---|---|
| GET | /api/review/{id}/replies | Get all replies to a review (chronological) |
| POST | /api/reviews/{page_id} | Create reply (include parent_id in body) |
| Field | Type | Default | Description |
|---|---|---|---|
text | string | - | Review comment (required) |
author | string | "anonymous" | Reviewer name |
tag | string | "general" | "general", "bug", "suggestion", or "question" |
metadata | object | - | Annotation context (element, selector, styles, etc.) |
parent_id | integer | - | Parent review ID for threaded replies |
| Field | Type | Description | |
|---|---|---|---|
status | "open" \ | "resolved" | Resolving auto-sets resolved_at and resolved_by |
text | string | Updated comment text | |
tag | string | Updated tag | |
resolved_by | string | Who resolved it (default: "user" via API, "agent" via MCP) | |
metadata | object | Updated annotation metadata |
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:
| File | Purpose |
|---|---|
reviews.db | SQLite database (commit to git to share reviews with your team) |
.gitkeep | Ensures directory is tracked |
.gitignore | Ignores WAL temp files (*.db-wal, *.db-shm) |
Path resolution:
REVIEW_DB_PATH env var (explicit override)PROJECT_ROOT/.reviews/reviews.db (default)./reviews.db (fallback)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'
Only the beginning is shown; read the rest in the repo