About pixasso
pixasso is an MCP server for developers and AI agents coordinating frontend design and engineering. It combines intent discovery, design references, architecture planning, design audits and viewport test plans.
Key features
- 01Project intent discovery across 16 pillars
- 02Search and fetch design references
- 03Generate design tokens and architecture graphs
- 04Audit layouts for AI design anti-patterns
- 05Create multi-viewport QA plans
Use cases
- 01Turn a frontend brief into tailored design directions
- 02Verify reference pages before using them
- 03Review markup and styling for design anti-patterns
- 04Plan responsive QA across viewport sizes
MCP support
Exposes frontend design and engineering tools to MCP clients over local stdio or hosted Streamable HTTP. The tools cover intent discovery, references, design-token generation, architecture graphs, audits and testing plans.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
6Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| description | string | Yes | Initial brief or description of the project. |
| targetAudience | string | No | Target audience or user persona if known. |
| projectArchetype | enum | Yes | The primary archetype of the frontend project.full_web_app | editorial_landing_page | creative_3d_canvas | design_system | general |
Details
From the project READMEpixasso-mcp
Model Context Protocol (MCP) server for Pixasso: the complete end-to-end frontend engineering and design orchestrator for AI agents and developers.
Pixasso bridges visionary art direction with robust frontend architecture across 16 foundational engineering pillars. It gives LLMs, coding assistants, and autonomous agents the ability to dynamically discover user intent, validate design tokens, compile Graphify-style architecture decision graphs, critique layouts against AI tropes, search 40 reference catalogs, and generate automated multi-viewport testing matrices.
Live Showcase & Specifications: https://pixasso.erebuzzz.tech or https://pixasso-two.vercel.app
System Architecture
flowchart TD
User["Developer / AI Agent Prompt"] --> Client["MCP Client (Claude / Cursor / VS Code / Antigravity)"]
Client --> Server["pixasso-mcp Server (Stdio / Remote HTTP)"]
subgraph Tools ["Exposed Tools (JSON-RPC)"]
T1["pixasso_discover_intent"]
T2["pixasso_search_references"]
T3["pixasso_fetch_reference"]
T4["pixasso_generate_genome"]
T5["pixasso_generate_brain"]
T6["pixasso_audit_design"]
T7["pixasso_generate_test_plan"]
T8["pixasso_explore_taste"]
T9["pixasso_seed_taste"]
end
Server --> Tools
subgraph TasteBrain ["Taste Exploration Engine & Decentralized Swarm"]
Router["TasteInferenceRouter<br/>(NVIDIA Nemotron 3 Ultra / Workers AI)"]
D1["Cloudflare D1 SQL<br/>(pixasso-taste-db)"]
KV["Cloudflare KV Edge Cache<br/>(taste:swarm:bundle)"]
end
T1 --> Router
T2 --> P2["40 Deep Reference Catalogs<br/>(Typography, Shaders, Layouts)"]
T3 --> P3["Live DOM & Content Extraction<br/>(Linkedom, Readability, SPA Detection)"]
T4 --> P4["Design Genome Specification<br/>(YAML Tokens, Verified References)"]
T5 --> P5["Design Brain DAG<br/>(Mermaid Decision Graph)"]
T6 --> P6["Objective Critique Engine<br/>(5-Pillar Scorecard)"]
T7 --> P7["Automated Interface QA<br/>(390px, 768px, 1024px, 1440px)"]
T8 --> D1
T8 --> KV
T9 --> D1
Deployment & Connection Transports
Pixasso MCP ships with dual transport architectures side by side:
- Local Stdio (npm): Runs locally on your machine via stdio with zero network latency.
- Hosted Remote (Cloudflare Workers): Serverless Streamable HTTP endpoint secured via GitHub OAuth, requiring zero local runtime dependencies.
1. Hosted Remote Endpoint (Streamable HTTP)
Connect any remote-compatible MCP client directly to:
https://mcp.pixasso.erebuzzz.tech/mcp
Connecting will open a GitHub OAuth prompt (read:user, user:email) to authorize your session. Each authenticated GitHub account receives a daily allowance of 200 tool calls.
2. Local Stdio Quick Start
Run instantly without local installation:
npx -y pixasso-mcp
Or install globally:
npm install -g pixasso-mcp
Client Integration
1. Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"pixasso-local": {
"command": "npx",
"args": ["-y", "pixasso-mcp"]
},
"pixasso-remote": {
"url": "https://mcp.pixasso.erebuzzz.tech/mcp"
}
}
}
2. Cursor
Add to your Cursor MCP settings (~/.cursor/mcp.json):
{
"mcpServers": {
"pixasso-local": {
"command": "npx",
"args": ["-y", "pixasso-mcp"]
},
"pixasso-remote": {
"url": "https://mcp.pixasso.erebuzzz.tech/mcp"
}
}
}
3. VS Code
Add to .vscode/mcp.json (for native VS Code MCP and GitHub Copilot) or your extension settings (Cline, Roo Code, Continue):
{
"mcpServers": {
"pixasso-local": {
"command": "npx",
"args": ["-y", "pixasso-mcp"]
},
"pixasso-remote": {
"url": "https://mcp.pixasso.erebuzzz.tech/mcp"
}
}
}
4. Claude Code CLI
Register local or remote:
# Local stdio
claude mcp add pixasso npx -y pixasso-mcp
# Remote HTTP
claude mcp add pixasso-remote --transport http https://mcp.pixasso.erebuzzz.tech/mcp
5. Google Antigravity & Gemini CLI
Add to ~/.gemini/antigravity/mcp_config.json:
{
"mcpServers": {
"pixasso": {
"command": "npx",
"args": ["-y", "pixasso-mcp"]
},
"pixasso-remote": {
"url": "https://mcp.pixasso.erebuzzz.tech/mcp"
}
}
}
6. Agent Installation Prompt (Install in Any IDE via AI Assistant)
You can prompt any AI coding assistant in your IDE (Cursor, VS Code, Windsurf, Claude, Copilot, Cline, Roo Code, Antigravity) to configure Pixasso automatically. Simply copy and paste the prompt below into your assistant chat:
Please configure the Pixasso MCP server for my project and editor.
Choose one of the two options:
1. Option A (Hosted Remote, zero local runtime):
Configure MCP server "pixasso-remote" with URL:
https://mcp.pixasso.erebuzzz.tech/mcp
2. Option B (Local Stdio):
Configure MCP server "pixasso" with command "npx" and args ["-y", "pixasso-mcp"]
Add the configuration to the appropriate MCP settings file for this editor (such as .vscode/mcp.json, ~/.cursor/mcp.json, claude_desktop_config.json, or cline_mcp_settings.json) and verify that all 9 Pixasso design and architecture tools are active.
Exposed MCP Tools
Every tool conforms to the official Model Context Protocol specification and declares all four directory hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint):
| Tool | Purpose | Key Inputs | Hints |
|---|---|---|---|
pixasso_discover_intent | Adaptive inquiry synthesizer across 16 pillars and brand genesis, powered by the Taste Inference Engine. Synthesizes 3 bespoke aesthetic worlds with compulsory popup questions. | projectArchetype, description, targetAudience, hasBrandIdentity, referenceUrls | readOnly, idempotent |
pixasso_search_references | Search across 40 curated design & architecture catalogs. | query, category, tag | readOnly, idempotent |
pixasso_fetch_reference | Fetches live HTML, extracts title/headings/readable text, detects client SPAs, and caches verified fetches. | url, focus | readOnly, openWorld |
pixasso_generate_genome | Compiles tokens, color ramps, typography, and libraries into design-genome.yaml. Enforces programmatic hard gate on verified references. | projectName, themeMode, groundTone, typography, colorTokens, references | readOnly, idempotent |
pixasso_generate_brain | Synthesizes a visual Graphify Mermaid decision graph and Task DAG. | projectName, decisions, tasks | readOnly, idempotent |
pixasso_audit_design | Evaluates markup and styling against AI design anti-patterns. | componentMarkup, contextDescription | readOnly, idempotent |
pixasso_generate_test_plan | Produces multi-viewport QA plans (390px, 768px, 1024px, 1440px). | projectName, testUrl, testedViewports | readOnly, idempotent |
pixasso_explore_taste | Explores the living Design Taste Graph across 12 movements and community-seeded directions without generic AI tropes. | query, movement, archetype, includeSwarm, limit | readOnly, idempotent |
pixasso_seed_taste | Anonymously seeds sanitized high-craft design tokens to the decentralized Taste Swarm with strict opt-in consent. | archetype, movement, typographyTokens, paletteTokens, layoutTokens, motionTokens, uisfxTokens, consentGiven | openWorld, idempotent |
Tool Scope & Design Integrity Hard Gates
pixasso_discover_intent(Taste Inference & Adaptive Question Picker): Formulates 3 bespoke aesthetic worlds tailored directly to your project brief using free multi-provider LLM routing (NVIDIA Nemotron 3 Ultra, OpenRouter free models, Workers AI, or 12 foundational movements). The returnedcompulsoryPopupQuestionsinclude brand gates, domain decisions, and the decentralized taste swarm consent choice for presentation viaask_question.pixasso_explore_taste(Living Taste Graph): Queries curated movements and community seeds. Returns typography pairings, WCAG-evaluated palettes, layout geometries, and micro-interaction audio cues.pixasso_seed_taste(Consent-Gated Swarm Seeding): Allows client nodes to anonymously seed sanitized design tokens back to Cloudflare D1. Zero code or private text is ever transmitted.pixasso_fetch_reference(Real Content Deconstruction): Autonomous models often hallucinate visual traits from domain names alone.pixasso_fetch_referenceinspects live pages, extracting DOM headings, metadata, visible links, and readable text via Mozilla Readability. If the page is an empty client SPA shell (under 200 characters of text), it flagsrenderedContentDetected: falseso agents do not fabricate visual descriptions.- Reference Gate on
pixasso_generate_genome: Any reference URL supplied topixasso_generate_genomemust first be verified throughpixasso_fetch_referencein the active session. If an unfetched URL is passed, the tool rejects the call with an informative error. Furthermore, unrendered SPA shells cannot claimepistemicStatus: 'known'without screenshot verification.
Architecture Lifecycle
sequenceDiagram
autonumber
participant Agent as Autonomous Agent
participant MCP as pixasso-mcp
participant Engine as Design Engine
Agent->>MCP: pixasso_discover_intent(projectType)
MCP-->>Agent: 16-Pillar Clarification Matrix & Brand Gate
Agent->>Agent: Interactive User Alignment (ask_question)
Agent->>MCP: pixasso_generate_genome(alignedSpecs)
MCP-->>Agent: Validated design-genome.yaml
Agent->>MCP: pixasso_generate_brain(decisions)
MCP-->>Agent: Mermaid Decision Map & Component DAG
Agent->>Engine: Component Fabrication (Semantic HTML5 / CSS / React)
Agent->>MCP: pixasso_audit_design(componentMarkup)
MCP-->>Agent: 5-Pillar Scorecard & Anti-Pattern Check
Agent->>MCP: pixasso_generate_test_plan(viewports)
MCP-->>Agent: Multi-Viewport Overflow Matrix (390px to 1440px)
The 16 Architecture Pillars
Pixasso orchestrates 16 distinct engineering disciplines:
- UI and Visual Design: Ground tone, contrast geometry, and materiality.
- Semantic HTML5 & JSX: Meaningful DOM hierarchies and ARIA roles.
- Modern CSS & Tailwind: Custom properties, container queries, and subgrid layouts.
- TypeScript & JS Logic: Strict typing, immutable schemas, and runtime contracts.
- Framework Architecture: React, Next.js, Svelte, Vue, and Astro paradigms.
- State Management: Zustand, Redux Toolkit, signals, and context boundaries.
- API & WebSockets: Streaming endpoints, SSE telemetry, and real-time state.
- Client Auth UX: Optimistic sessions, token lifecycle, and secure storage.
- Forms & Zod Validation: Type-safe schema validation and real-time feedback.
- Motion & 3D WebGL: Three.js shaders, CSS hardware transforms, and WebGPU.
- Responsive Multi-Device Design: Viewport sweeps at 390px, 768px, 1024px, and 1440px.
- WCAG AA/AAA Accessibility: Keyboard navigation, focus rings, and screen-reader testing.
- Core Web Vitals: INP, LCP, CLS optimizations, and asset tree-shaking.
- Testing Architecture: Vitest, Playwright, and automated overflow checks.
- Tooling & DX: ESLint, Prettier, Vite, and automated CI pipelines.
- Edge Deployment: Immutable releases on GitHub Pages, Vercel, and Cloudflare.
Living Taste Brain & Swarm Memory (Daily Edge Sync)
Pixasso MCP features an autonomous exploration layer and decentralized "Taste Swarm" inspired by BitTorrent seeding. Rather than asking repetitive questions or defaulting to generic AI tropes, Pixasso continuously explores design movements, synthesizes bespoke aesthetic worlds, and learns high-craft token combinations from consented peer nodes at zero financial cost.
Living Swarm Memory Status
- Storage: Cloudflare D1 Serverless SQL (
pixasso-taste-db) - Edge Cache: Global Cloudflare KV (
taste:swarm:bundle) - Daily Memory Consolidation: Runs at 00:00 UTC via Cloudflare Workers Cron and GitHub Actions
- Live Memory Endpoint:
https://mcp.pixasso.erebuzzz.tech/taste/brain
graph TD
subgraph SwarmMemoryCore ["Living Taste Brain & Swarm Core"]
Core["Swarm Memory Nexus<br/>- D1 Relational Engine<br/>- Daily Memory Sync"]
end
subgraph ActiveClusters ["Top Learned Aesthetic Clusters"]
C1["Swiss International & Grotesk<br/>- Geometry: Rigid 12-col grid<br/>- Contrast: 18.2:1<br/>- Weight: 14%"]
C2["Warm Editorial Poise<br/>- Geometry: Split-screen column<br/>- Serif: Newsreader + Mono<br/>- Weight: 12%"]
C3["Retro-Futurist Monospace HUD<br/>- Ground: CRT Dark (#080b09)<br/>- Display: JetBrains Mono<br/>- Weight: 11%"]
C4["Neo-Brutalism & High Contrast<br/>- Geometry: Asymmetric Bento<br/>- Borders: 2px Solid Ink<br/>- Weight: 10%"]
C5["Bio-Digital Solarpunk<br/>- Ground: Earth Stone (#f4f3ef)<br/>- Motion: Organic Spring<br/>- Weight: 9%"]
end
subgraph LearningPipeline ["Daily Swarm Convergence"]
T1["Decentralized Peer Seeds<br/>- Anonymized Design Tokens"] --> AntiTrope["Quality Gate Heuristic<br/>- Anti-Trope & Contrast Filter"]
AntiTrope --> Core
Core --> C1
Core --> C2
Core --> C3
Core --> C4
Core --> C5
Core --> EdgeKV["Edge KV Distribution Cache<br/>- Sub-millisecond Latency"]
end
Zero-Cost Inference Router: Are API Keys Required?
No. You do NOT need any API keys to use Pixasso MCP.
Pixasso MCP is built with a tiered fallback architecture designed to remain completely free for developers and agents out of the box:
| Tier | Provider / Engine | API Key Requirement | Purpose & Fallback Behavior |
|---|---|---|---|
| Tier 1 | NVIDIA NIM (nvidia/nemotron-3-ultra-550b) | Optional (Server Secret) | Advanced artistic direction and unconventional palette generation. NVIDIA offers 1,000 free trial credits at build.nvidia.com. If unset, instantly skips to Tier 2. |
| Tier 2 | OpenRouter Free Tier (llama-3.3-70b-instruct:free, gemini-2.0-flash-exp:free) | Optional (Server Secret) | Free multi-model inference. Requires only a free OpenRouter account with $0 balance. If unset, instantly skips to Tier 3. |
| Tier 3 | Cloudflare Workers AI (@cf/meta/llama-3.3-70b-instruct) | None (Built-in) | Runs directly on the Cloudflare edge via the Worker AI binding. Cloudflare provides 10,000 free neurons daily with zero external keys required. |
| Tier 4 | Foundational Design Graph (12 Curated Movements) | None (100% Offline) | Deterministic design pairing across 12 high-taste movements. Operates with zero network calls, zero latency, and zero token costs. |
For Local Stdio Users (npx -y pixasso-mcp)
You do not need to provide any API keys or configuration files. The local stdio server will run the offline foundational graph and local rules with zero cloud dependency.
For Self-Hosters Deploying Their Own Remote Worker
If you deploy your own instance of the Cloudflare Worker and wish to connect NVIDIA NIM or OpenRouter, you can optionally store secrets using Wrangler:
# Optional: Set NVIDIA NIM API key
npx wrangler secret put NVIDIA_API_KEY
# Optional: Set OpenRouter API key
npx wrangler secret put OPENROUTER_API_KEY
If you omit these secrets, your worker will seamlessly use Cloudflare Workers AI and the offline foundational graph with zero errors.
Resources & Prompts
Resources (pixasso://)
pixasso://references/{catalogName}: Direct read access to all 29 reference catalogs including typography systems, motion choreography, sound design, and shader parameters.pixasso://templates/{templateName}: Access to all 11 production blueprints includingdesign-genome.yaml,interface-test-plan.md, andcomponent-implementation-spec.md.
Prompts (mcp://prompts/)
intent-discovery: Prompt for launching adaptive user interviews without form fatigue.frontend-architecture: Scaffold complete 16-pillar architecture blueprints.design-critique: Run rigorous design audits to identify and eliminate AI visual tropes.typography-direction: Formulate harmonious display, serif, and monospace pairings.interface-qa: Execute multi-device viewport tests and sensory verification.
License & Privacy
- License: MIT (c) Erebuzzz. See LICENSE.
- Privacy Policy: Zero telemetry, zero prompt recording, ephemeral in-memory processing. See PRIVACY.md.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.