GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Descripción del creador (original en inglés)
Human-to-AI code review bridge. Review UI in the browser, AI agents fix code via MCP.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
PROJECT_ROOT, REVIEW_PORTNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"ui-ticket": {
"command": "uvx",
"args": [
"ui-ticket-mcp"
],
"env": {
"PROJECT_ROOT": "your-value",
"REVIEW_PORT": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add ui-ticket --env PROJECT_ROOT=your-value --env REVIEW_PORT=your-value -- uvx ui-ticket-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"ui-ticket": {
"command": "uvx",
"args": [
"ui-ticket-mcp"
],
"env": {
"PROJECT_ROOT": "your-value",
"REVIEW_PORT": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"ui-ticket": {
"type": "stdio",
"command": "uvx",
"args": [
"ui-ticket-mcp"
],
"env": {
"PROJECT_ROOT": "your-value",
"REVIEW_PORT": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
REVIEW_PORT envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub 0ics-srls, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: PROJECT_ROOT
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.6.2) llegó al registro ayer.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: GitHub, Desktop Commander, Cloudflare MCP
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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'
Solo se muestra el principio; lee el resto en el repo