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Pixasso

by Erebuzzzversion 1.0.4i★ –iRuns on your computer
Registry nameio.github.Erebuzzz/pixasso

Install

Overview

Description from the maker (original English)

End-to-end frontend engineering and design orchestrator across 16 foundational pillars.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

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": {
    "pixasso": {
      "command": "npx",
      "args": [
        "-y",
        "pixasso-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add pixasso -- npx -y pixasso-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "pixasso": {
      "command": "npx",
      "args": [
        "-y",
        "pixasso-mcp"
      ]
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "pixasso": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "pixasso-mcp"
      ]
    }
  }
}

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.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Erebuzzz, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

  • More stars than 0% of the other 2186 servers in this category
  • Published to the registry more recently than 36% of the other 2186 servers in this category
  • Basic checks equal to or better than 100% of the other 2186 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Pixasso safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.4) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago
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Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago
Install

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago
Install

README from the maker

Open the README

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.

pixasso-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 (NVIDIA Nemotron 3 Ultra / Workers AI)"] D1["Cloudflare D1 SQL (pixasso-taste-db)"] KV["Cloudflare KV Edge Cache (taste:swarm:bundle)"] end

T1 --> Router T2 --> P2["40 Deep Reference Catalogs (Typography, Shaders, Layouts)"] T3 --> P3["Live DOM & Content Extraction (Linkedom, Readability, SPA Detection)"] T4 --> P4["Design Genome Specification (YAML Tokens, Verified References)"] T5 --> P5["Design Brain DAG (Mermaid Decision Graph)"] T6 --> P6["Objective Critique Engine (5-Pillar Scorecard)"] T7 --> P7["Automated Interface QA (390px, 768px, 1024px, 1440px)"] T8 --> D1 T8 --> KV T9 --> D1


Deployment & Connection Transports

Pixasso MCP ships with dual transport architectures side by side:

  1. Local Stdio (npm): Runs locally on your machine via stdio with zero network latency.
  2. 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
  1. 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):

ToolPurposeKey InputsHints
pixasso_discover_intentAdaptive 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, referenceUrlsreadOnly, idempotent
pixasso_search_referencesSearch across 40 curated design & architecture catalogs.query, category, tagreadOnly, idempotent
pixasso_fetch_referenceFetches live HTML, extracts title/headings/readable text, detects client SPAs, and caches verified fetches.url, focusreadOnly, openWorld
pixasso_generate_genomeCompiles tokens, color ramps, typography, and libraries into design-genome.yaml. Enforces programmatic hard gate on verified references.projectName, themeMode, groundTone, typography, colorTokens, referencesreadOnly, idempotent
pixasso_generate_brainSynthesizes a visual Graphify Mermaid decision graph and Task DAG.projectName, decisions, tasksreadOnly, idempotent
pixasso_audit_designEvaluates markup and styling against AI design anti-patterns.componentMarkup, contextDescriptionreadOnly, idempotent
pixasso_generate_test_planProduces multi-viewport QA plans (390px, 768px, 1024px, 1440px).projectName, testUrl, testedViewportsreadOnly, idempotent
pixasso_explore_tasteExplores the living Design Taste Graph across 12 movements and community-seeded directions without generic AI tropes.query, movement, archetype, includeSwarm, limitreadOnly, idempotent
pixasso_seed_tasteAnonymously seeds sanitized high-craft design tokens to the decentralized Taste Swarm with strict opt-in consent.archetype, movement, typographyTokens, paletteTokens, layoutTokens, motionTokens, uisfxTokens, consentGivenopenWorld, 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 returned compulsoryPopupQuestions include brand gates, domain decisions, and the decentralized taste swarm consent choice for presentation via ask_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_reference inspects 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 flags renderedContentDetected: false so agents do not fabricate visual descriptions.
  • Reference Gate on `pixasso_generate_genome`: Any reference URL supplied to pixasso_generate_genome must first be verified through pixasso_fetch_reference in the active session. If an unfetched URL is passed, the tool rejects the call with an informative error. Furthermore, unrendered SPA shells cannot claim epistemicStatus: '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:

  1. UI and Visual Design: Ground tone, contrast geometry, and materiality.
  2. Semantic HTML5 & JSX: Meaningful DOM hierarchies and ARIA roles.
  3. Modern CSS & Tailwind: Custom properties, container queries, and subgrid layouts.
  4. TypeScript & JS Logic: Strict typing, immutable schemas, and runtime contracts.
  5. Framework Architecture: React, Next.js, Svelte, Vue, and Astro paradigms.
  6. State Management: Zustand, Redux Toolkit, signals, and context boundaries.
  7. API & WebSockets: Streaming endpoints, SSE telemetry, and real-time state.
  8. Client Auth UX: Optimistic sessions, token lifecycle, and secure storage.
  9. Forms & Zod Validation: Type-safe schema validation and real-time feedback.
  10. Motion & 3D WebGL: Three.js shaders, CSS hardware transforms, and WebGPU.
  11. Responsive Multi-Device Design: Viewport sweeps at 390px, 768px, 1024px, and 1440px.
  12. WCAG AA/AAA Accessibility: Keyboard navigation, focus rings, and screen-reader testing.
  13. Core Web Vitals: INP, LCP, CLS optimizations, and asset tree-shaking.
  14. Testing Architecture: Vitest, Playwright, and automated overflow checks.
  15. Tooling & DX: ESLint, Prettier, Vite, and automated CI pipelines.
  16. Edge Deployment: Immutable releases on GitHub Pages, Vercel, and Cloudflare.

Living

Only the beginning is shown; read the rest in the repo

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