UI Architect AI

From idea to world-class design stack in seconds.

A comprehensive Design Intelligence System — self-updating multi-agent architecture
that discovers the best components, animations, libraries, colors, typography, icons,
mobile UI patterns, and design inspirations for any web or mobile project.

7 applications · 3 shared packages · 9 specialist agents · 2200+ curated resources

Built with · TypeScript · Node.js · Next.js · Prisma · PostgreSQL · MCP SDK

Project Overview

The Intelligence Network

CLI · MCP Server · Web Dashboard · VS Code Extension

graph TD
    User[User / Developer] --> Dashboard[Web Dashboard Next.js]
    User --> VSCode[VS Code Extension]
    User --> CLI[CLI Tool uia]
    User --> AIClient[AI Coding Agents<br/>Claude / Cursor / Gemini]

    Dashboard --> ServerActions[Server Actions]
    VSCode --> MCPClient[MCP Client]
    CLI --> RecEngine[Recommendation Engine]
    AIClient --> MCPServer[MCP Server v2.0]

    MCPServer --> RecEngine
    ServerActions --> RecEngine

    RecEngine --> Architect[Design Architect Agent]
    Architect --> Agents[9 Specialist Agents]

    Agents --> KB[(Knowledge Base<br/>knowledge-base.json)]

    AutoDisc[Auto Discovery<br/>cron scheduler] --> Research[Research Agent]
    Research --> Internet[External Sources<br/>21st.dev, Magic UI, GitHub]

    ReviewAI[Design Review AI] --> Architect
    ReviewAI --> RecEngine

    subgraph "Data Flow"
        Agents
        KB
        Research
    end

Interface Gallery

Terminal CLI (uia)

MCP in Cursor

Features

Multi-Agent Intelligence 9 specialized agents rank resources by project intent using a weighted scoring formula — 50% intent match, 30% quality heuristics, 20% popularity.	MCP Server v2.0 4 tools exposed via Model Context Protocol for Claude Code, Cursor, Gemini, Roo Code, and Cline — `recommend_design`, `analyze_design`, `find_components`, `get_latest_audit`.	Developer Level Personalization Results adapt to beginner, intermediate, or advanced skill levels — beginners get simpler resources, experts get advanced customizable options.
Web Dashboard Next.js 16 with dark mode, live prompt generation, responsive card grids, and sidebar navigation for visual design exploration.	CLI Tool Terminal interface with color-coded output, spinner feedback, and 5 commands — `recommend`, `search`, `find`, `analyze`, `prompt`.	VS Code Extension Sidebar webview, command-palette recommendations, secure sandboxed webviews with CSP, and dark theme integration.
Research Agent Automated discovery engine with URL/name deduplication, category coverage analysis, and 4 markdown reports per scan.	Auto Discovery Periodic cron scheduler — daily research scans, weekly link validation via HTTP HEAD, monthly score refresh aligned with trends.	Design Review AI Heuristic visual analysis engine providing overall, accessibility, and visual quality scores with actionable suggestions and component recommendations.
100+ Parallel Agents Orchestrator dispatches to all 9 agents simultaneously — results merged, deduplicated, and sorted in under 200ms.	Deterministic Results Same prompt + same knowledge base = identical results every time. No randomness in the scoring pipeline.	Scoring Formula `0.5matchScore + 0.3qualityScore + 0.2*popularityScore` — framework, style, use case match + accessibility, performance, popularity signals.

Project Structure

ui-architect-ai/
│
├── apps/                              # Application ecosystem (7 apps)
│   ├── cli/                          # Terminal CLI (uia) — 5 commands
│   │   └── src/index.ts
│   ├── mcp-server/                    # MCP v2.0 server — 4 tools
│   │   └── src/index.ts
│   ├── dashboard/                     # Next.js 16 web dashboard
│   │   └── src/app/
│   ├── vscode-extension/              # VS Code sidebar + commands
│   │   └── src/extension.ts
│   ├── research-agent/                # Automated discovery engine
│   │   └── src/index.ts
│   ├── auto-discovery/                # Cron maintenance scheduler
│   │   └── src/index.ts
│   └── design-review-ai/              # Visual analysis engine
│       └── src/index.ts
│
├── packages/                          # Shared libraries (3 packages)
│   ├── core/                          # Domain types, interfaces, logger
│   │   └── src/index.ts
│   ├── database/                      # Prisma client, schema, seed
│   │   └── prisma/schema.prisma
│   └── recommendation-engine/          # Multi-agent recommendation system
│       └── src/agents/               # Orchestrator + 9 specialist agents
│
├── data/                              # Centralized intelligence data
│   ├── knowledge-base.json           # Primary DB (~2264 resources)
│   └── internal_resources.json       # Secondary DB (~2240 resources)
│
├── docs/                              # Documentation
│   ├── architecture/                 # DB design, schema, ER diagram
│   ├── guides/                       # Setup, MCP tools spec
│   ├── rules/                        # Coding standards & global rules
│   ├── NETWORK_MAP.md
│   └── COMPLETED_PHASES.md
│
├── package.json                      # Monorepo root (npm workspaces)
├── tsconfig.json                     # ES2022, NodeNext, strict mode
├── .gitignore
├── technical-debt.md
├── missing-features.md
└── architecture-review.md

Technology Stack

Layer	Technologies
Monorepo	npm workspaces
Runtime	Node.js 20+, TypeScript 5.3+ (strict mode across all 7 apps + 3 packages)
CLI	commander · chalk · ora
MCP	@modelcontextprotocol/sdk v1.0.1 — Stdio transport, JSON-RPC 2.0
Dashboard	Next.js 16.2.9 · React 19.2.4 · Tailwind CSS v4 · Framer Motion · Lucide React · TanStack React Query
VS Code	@types/vscode 1.85+ · Webview API with sandboxed CSP
Database	PostgreSQL · Prisma 7.8
Scheduling	node-cron
HTTP	axios
Tooling	tsx · ESLint

Getting Started

Prerequisites

Node.js	v20 or higher
npm	v10 or higher (workspaces support)
PostgreSQL	Optional — system runs with just the JSON knowledge base

Quick Install

# 1. Install all dependencies across all 10+ packages/apps
npm install

# 2. Compile TypeScript to JavaScript
npm run build

Database Setup — Optional

Expand for Prisma/PostgreSQL setup

# Create .env in root
echo 'DATABASE_URL="postgresql://user:password@localhost:5432/ui_architect_db"' > .env

# Initialize schema
cd packages/database
npx prisma generate
npx prisma db push
npx prisma studio    # Verify tables interactively

MCP Server — AI Agent Integration

The MCP server lets AI coding agents query the design intelligence system directly via 4 tools over Stdio JSON-RPC 2.0.

Running the Server

node apps/mcp-server/dist/index.js

Connecting AI Clients

Client	Configuration
Cursor	Settings → Features → MCP → Add: `node /abs/path/to/apps/mcp-server/dist/index.js`
Claude Code	`claude mcp add ui-architect -- node /abs/path/to/apps/mcp-server/dist/index.js`
Gemini CLI	`gemini-cli mcp register ui-architect -- node /abs/path/to/apps/mcp-server/dist/index.js`
Roo Code / Cline	Add to `mcpServers` config as `command` type with the node path

Exposed Tools

Tool	Input	Output
`recommend_design`	`{ prompt, developerLevel? }`	`RecommendationStack` — components, animations, icons, typography, colors, mobileUI, inspirations
`analyze_design`	`{ type: "url"\|"screenshot", value }`	`DesignReviewResult` — scores, issues, suggestions, recommendations
`find_components`	`{ query }`	Filtered component resources
`get_latest_audit`	`{}`	Latest gap-analysis & audit report markdown

Verify Connection

npx tsx apps/mcp-server/src/test-client.ts

CLI Usage

Command	Description
`uia recommend <prompt>`	Get design recommendations with optional `--level` flag
`uia search <query>`	Search across all design resources
`uia find <category> <query>`	Find resources in a specific category
`uia analyze`	Analyze project for design debt (stub — coming soon)
`uia prompt <type>`	Generate AI prompt templates for design tasks

# Get design recommendations
npx tsx apps/cli/src/index.ts recommend "Modern SaaS Dashboard"

# With developer level filtering
npx tsx apps/cli/src/index.ts recommend "Bento Grid Portfolio" --level advanced

# Search across all resources
npx tsx apps/cli/src/index.ts search "glassmorphism UI kit"

# Find resources in a specific category
npx tsx apps/cli/src/index.ts find animations "scroll reveal"

Output: Color-coded by category — cyan (components), yellow (animations), green (icons), magenta (typography), blue (colors), red (mobileUI). Each entry shows name, description, and URL.

Web Dashboard

npm run dev --workspace=dashboard

Navigate to http://localhost:3000. Enter a design prompt and get categorized results in a responsive card grid. Features include:

Dark mode with Tailwind CSS v4 theming
Popular prompt suggestions (Developer Portfolio, Bento Dashboard, E-commerce)
Server-side rendering via Next.js Server Actions
Sidebar navigation with active state

VS Code Extension

cd apps/vscode-extension
npm run watch

Open VS Code → Run Extension → Use the UI Architect sidebar panel or run UI Architect: Recommend from the command palette.

Multi-Agent Recommendation System

Scoring Formula

totalScore = 0.5 × matchScore + 0.3 × qualityScore + 0.2 × popularityScore

Component	Signals
matchScore	Framework match (+10) · Style match (+8) · Use case match (+8) · Prompt keyword match (+5 exact, +2 description) · Domain bonuses
qualityScore	Baseline 75 · Accessibility/WCAG (+10) · Performance (+10) · Responsive/mobile (+5) · Capped at 100
popularityScore	Baseline 60 · "popular"/"standard" (+15) · "tailwind"/"shadcn" (+20) · Capped at 100

9 Specialist Agents

Agent	Domain	Special Bonuses
ComponentAgent	Components, UI kits	Framework match (+10), playground (+5), accessible (+8)
AnimationAgent	Animations, motion	Physics-based (+5)
TypographyAgent	Fonts, typography	Variable fonts (+5), self-hosted/open-source (+3)
ColorAgent	Colors, gradients	WCAG/contrast (+10)
IconAgent	Icons	SVG/open-source (+5)
MobileUIAgent	iOS, Android, Flutter, RN	Platform match (+10)
InspirationAgent	Galleries, showcases	Gallery/showcase (+5)
TrendAgent	All resources	Recency 2024-2026 (+5), trend keywords (+15)
ResourceResearchAgent	All resources	Broad keyword match (+2 per word)

Developer Level Personalization

Level	Behavior
Beginner	Bonuses for "simple", "easy", "starter" resources · Penalties for "advanced", "complex"
Intermediate	Neutral — standard professional stacks
Advanced	Bonuses for "customizable", "3D", "physics-based", "complex" · Penalties for "simple"

Research Agent & Auto Discovery

Research Agent

The automated discovery engine reads the knowledge base, simulates internet research (scanning 21st.dev, Magic UI, GitHub), deduplicates by URL and name, and generates 4 markdown reports:

Report	Content
`research-report.md`	Summary statistics of the scan
`new-resources.md`	Newly discovered resources with metadata
`duplicate-report.md`	Duplicate resources found (matched by name/URL)
`gap-analysis.md`	Category coverage counts and missing design areas

npm run dev --workspace=@ui-architect/research-agent

Auto Discovery — Maintenance Scheduler

Periodic cron-based maintenance for database integrity and freshness.

Schedule	Day/Time	Actions
Daily	Every day at 00:00	Research Agent scan
Weekly	Sunday at 01:00	Research scan + dead link validation (HTTP HEAD)
Monthly	1st at 02:00	Research scan + link validation + trend-based score refresh

# Start the daemon scheduler
npx tsx apps/auto-discovery/src/index.ts start

# Run a one-time scan
npx tsx apps/auto-discovery/src/index.ts run --mode daily
npx tsx apps/auto-discovery/src/index.ts run --mode weekly
npx tsx apps/auto-discovery/src/index.ts run --mode monthly

Design Review AI

Heuristic visual analysis engine providing design and accessibility scoring for any URL or screenshot.

Metric	Score	Notes
Overall Score	78/100	General design quality assessment
Accessibility	65/100	WCAG compliance, contrast, ARIA labels
Visual Quality	82/100	Typography, spacing, hierarchy, color harmony

npm run dev --workspace=@ui-architect/design-review-ai

Programmatic usage:

const engine = new DesignReviewEngine();
const result = await engine.analyze({ type: "url", value: "https://example.com" });
// => { overallScore: 78, accessibilityScore: 65, visualQualityScore: 82,
//      issues: [...], suggestions: [...], recommendations: {...} }

Database Schema

The database uses a hybrid extending-table architecture — a core Resource table with 1:1 extension tables per design category, avoiding a sparse monolithic table with 40+ nullable columns. 3NF compliant.

Core Tables

Table	Key Fields
Resource	`id` (UUID PK), `name`, `description`, `url`, `popularity`, `score`, `useCases[]`, `categoryId` (FK)
Category	`id` (UUID PK), `name` (unique), `description`?
Tag	`id` (UUID PK), `name` (unique) — M2M with Resource

Extension Tables — 1:1 with Resource

Table	Specialty Fields
Component	frameworks[], isResponsive, isAccessible, hasPlayground, codeSnippet, dependencies[]
Library	packageManager, installCommand, license, githubStars, bundleSizeKb, repoUrl
Animation	engine, isPhysicsBased, triggerType, durationMs, easing
Icon	formats[], iconCount, styles[], isCustomizable
Typography	fontType, designer, isVariable, licensing, isSelfHosted
ColorPalette	hexCodes[], contrastRatio, isWCAGCompliant, paletteType
MobileUI	platforms[], screenType, deviceMockUrl, userFlowSteps[]
Inspiration	submittedBy, inspirationUrl, screenshotUrl, stylesDetected[]

# Seed the database
npx tsx packages/database/src/seed.ts

Development

Running Apps

Component	Command
Web Dashboard	`npm run dev --workspace=dashboard`
CLI	`npx tsx apps/cli/src/index.ts recommend "prompt"`
MCP Server	`npx tsx apps/mcp-server/src/index.ts`
Design Review	`npm run dev --workspace=@ui-architect/design-review-ai`
Research Agent	`npm run dev --workspace=@ui-architect/research-agent`
Auto Discovery	`npm run scan:daily --workspace=@ui-architect/auto-discovery`
VS Code Extension	`cd apps/vscode-extension && npm run watch`

Testing

npm test                                    # All workspace tests
npx tsx packages/recommendation-engine/tests/agents.test.ts   # Agent logic
npx tsx apps/mcp-server/src/test-client.ts                     # MCP handshake
npx tsx apps/research-agent/tests/research.test.ts             # Research agent

Configuration Reference

Variable	Required	Default	Description
`DATABASE_URL`	For Prisma	—	PostgreSQL connection string
`UI_ARCHITECT_DB_PATH`	No	`data/knowledge-base.json`	Custom path to knowledge base JSON

Project Phases

Phase	Component	Status
1–2	Infrastructure, Database & Schema	✅ Complete
3	Recommendation Logic	✅ Complete
4	MCP Server v1	✅ Complete
5	Multi-Agent Hub — 9 agents + orchestrator	✅ Complete
6	Automated Research & Deduplication	✅ Complete
7	Next.js Web Dashboard	✅ Complete
8	VS Code / Cursor Integration	✅ Complete
9	Terminal CLI (uia)	✅ Complete
10	Maintenance & Link Health — Auto Discovery	✅ Complete
11	Visual Scoring & Accessibility Review	✅ Complete
12	Intelligence Network & Developer Personalization	✅ Complete

12 / 12 phases — 100% complete

Security

No Hardcoded Secrets	API keys and credentials are environment-variable based
XSS Protection	VS Code webview uses CSP with nonce-based scripts; textContent instead of innerHTML
Sandboxed Webviews	VS Code extension runs in sandboxed iframes with no node access
Stdio-Only MCP	No network layer exposed — MCP communicates exclusively over stdin/stdout
100% TypeScript Strict	Strict mode enabled across all 7 applications and 3 packages

License

MIT — Open source and free to use.

Built with the UI Architect AI monorepo · npm workspaces · TypeScript strict mode

Name		Name	Last commit message	Last commit date
.github		.github
apps		apps
data		data
docs		docs
packages		packages
photos		photos
reports		reports
scripts		scripts
.env.example		.env.example
.eslintrc.json		.eslintrc.json
.gitignore		.gitignore
.npmrc		.npmrc
.nvmrc		.nvmrc
.prettierrc		.prettierrc
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json

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UI Architect AI

Project Overview

The Intelligence Network

Interface Gallery

Terminal CLI (uia)

MCP in Cursor

Features

Multi-Agent Intelligence

MCP Server v2.0

Developer Level Personalization

Web Dashboard

CLI Tool

VS Code Extension

Research Agent

Auto Discovery

Design Review AI

100+ Parallel Agents

Deterministic Results

Scoring Formula

Project Structure

Technology Stack

Getting Started

Prerequisites

Quick Install

Database Setup — Optional

MCP Server — AI Agent Integration

Running the Server

Connecting AI Clients

Exposed Tools

Verify Connection

CLI Usage

Web Dashboard

VS Code Extension

Multi-Agent Recommendation System

Scoring Formula

9 Specialist Agents

Developer Level Personalization

Research Agent & Auto Discovery

Research Agent

Auto Discovery — Maintenance Scheduler

Design Review AI

Database Schema

Core Tables

Extension Tables — 1:1 with Resource

Development

Running Apps

Testing

Configuration Reference

Project Phases

Security

License

About

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Releases

Packages

Contributors

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