Pixasso

io.github.Erebuzzz由 GitHub 帳號 Erebuzzz 發布v1.0.4更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

Pixasso 引導助理完成前端設計工作:意圖探索、參考檢索、設計權杖、審查,以及多視埠測試計畫。

可以做什麼
Pixasso 提供九個工具,涵蓋前端設計流程。它依專案簡介生成美學方向與釐清問題,檢索 31 個精選設計目錄,並抓取即時頁面以擷取標題與可讀文字,同時標記內容為空的單頁應用程式外殼。它把設計權杖編譯成 design-genome 檔案,產生 Mermaid 決策圖,依 AI 設計反模式審查標記程式碼,並產出多視埠 QA 計畫。它也可查詢並選擇性地向共享設計品味圖譜提交資料。
適用情境
當助理協助前端或介面工作,需要結構化設計方向、經驗證的參考、權杖規格、版面審查或響應式測試計畫時適用。對後端、資料或非設計任務價值有限。
執行需求
透過 npm 套件 pixasso-mcp(npx -y pixasso-mcp)以 stdio 在本機執行,需要 Node.js;本機使用不需 API 金鑰或設定檔。另有託管遠端 HTTP 端點,需要 GitHub OAuth 登入,每個帳號每日 200 次工具呼叫額度。參考抓取與遠端使用需要網路存取。
安裝前請注意
提交工具會把去識別化的設計權杖傳送到共享雲端資料庫,且需要明確同意;README 稱不會傳輸程式碼或私密文字。參考抓取會存取第三方頁面,URL 會暴露給這些網站。遠端端點需要 GitHub OAuth 授權,並依帳號限制每日呼叫次數。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Pixasso,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

pixasso-mcp

Model Context Protocol (MCP) server for Pixasso: the complete end-to-end frontend engineering and design orchestrator for AI agents and developers.

[npm version] [License: MIT] [Node.js]

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

mermaid
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:

  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:

text
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:

bash
npx -y pixasso-mcp

Or install globally:

bash
npm install -g pixasso-mcp

Client Integration

1. Claude Desktop

Add to your claude_desktop_config.json:

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):

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):

json
{  "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:

bash
# Local stdioclaude mcp add pixasso npx -y pixasso-mcp
# Remote HTTPclaude mcp add pixasso-remote --transport http https://mcp.pixasso.erebuzzz.tech/mcp

5. Google Antigravity & Gemini CLI

Add to ~/.gemini/antigravity/mcp_config.json:

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:

text
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):

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

mermaid
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 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
mermaid
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:

TierProvider / EngineAPI Key RequirementPurpose & Fallback Behavior
Tier 1NVIDIA 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 2OpenRouter 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 3Cloudflare 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 4Foundational 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:

bash
# Optional: Set NVIDIA NIM API keynpx wrangler secret put NVIDIA_API_KEY
# Optional: Set OpenRouter API keynpx 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 including design-genome.yaml, interface-test-plan.md, and component-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.

來源:mcp-server/README.md,提交 e6ea3d3

工具

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版本歷史

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  1. v1.0.4最新Sep 22, 2026

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