技能潮 SkillTide 提交收录
官方说明7 个来源MCP 服务8 天前
Brand-System/brandsystem-mcp

Brand-System/brandsystem-mcp

Use your brand guidelines with AI @brandsystem/mcp turns the brand material you already have into context AI agents can use.** Give it a website, PDF guide, Figma library, local files, or a Brandcode Studio brand.
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add brandsystem-mcp -- npx -y brandsystem-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
15 ★ · Brand-System/brandsystem-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 15 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 Brand-System/brandsystem-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Use your brand guidelines with AI

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**@brandsystem/mcp turns the brand material you already have into context AI agents can use.** Give it a website, PDF guide, Figma library, local files, or a Brandcode Studio brand. It produces a portable .brand/ runtime with design tokens, voice rules, provenance, and compliance checks.
Local-first. No account required. The default Core profile exposes 12 tools covering the complete adopt → use → check loop.
Start here
Install it for your agent, then ask: **“How do I use my brand guidelines with AI?”**
install is a dry run unless you pass --write. Replace claude-code with cline, cursor, windsurf, or claude-desktop as needed. JSON-file targets preserve existing settings; Cline and Codex setup delegate to their official MCP commands so their current schemas remain authoritative. Agents can follow the compact installation guide without reading this entire README.
Already configured? Tell your agent:
> Use my existing brand guidelines with AI. Start from this website/PDF/Figma library and show me what needs human confirmation.
What It Solves
AI tools default to category-average output because they have no brand context. Brand guidelines live in PDFs, Figma files, and people's heads — none of which AI tools can read at the moment of creation. The dominant failure mode isn't "broken output"; it's "correct but generic" — output that passes mechanical checks but reads like a competent generalist could have made it.
This MCP server is the authoring half of the **"Two MCPs, One Brand"** model. It extracts brand identity from live sources, compiles it into a .brand/ directory with structured governance (anti-patterns, proof-point status, voice rules, application rules) plus DTCG tokens, brand-runtime.json, and interaction-policy.json. That directory is the **portable brand runtime** — the artifact that travels with your brand from surface to surface.
- **Claude Design** reads the .brand/ directory natively when pointed at a governed repo
- **Claude Code**, **Claude Desktop**, **Cursor**, and **Windsurf** connect to this server directly over stdio and load brand-runtime.json at generation time
- **ChatGPT** and other remote-first clients consume the same runtime as an uploaded artifact (brand-report.html / brand-runtime.json) or via a remote MCP connection — see Compatibility
- **@brandcode/mcp** (the hosted Use MCP) serves the same runtime over HTTP for teams that want authenticated live reads at mcp.brandcode.studio/{slug}
With brand-runtime.json loaded, agent prompts collapse from 200-400 tokens of inline brand context to just the delta. First output is on-brand. No review bottleneck.
---
Quick Start
1. Add to your MCP config
Copy this into .mcp.json (Claude Code), .cursor/mcp.json (Cursor), or Windsurf MCP settings. Codex users can run npx @brandsystem/mcp install --client codex --write instead:
2. Create your brand system
Tell your AI tool:
> Run brand_start with client_name="Acme Corp", website_url="https://acme.com", and mode="auto"
That single command extracts colors, fonts, and logo from the website, escalates to rendered or deeper multi-page extraction when the cheap pass is weak, compiles DTCG tokens, generates design-synthesis.json + DESIGN.md, and generates a portable HTML brand report -- all in under 60 seconds.
3. What you get
Load brand-runtime.json into any sub-agent's context. First output is on-brand. No per-prompt boilerplate.
4. Use it
> Run brand_write for a social-graphic about "Q3 product launch"
The AI now has your full brand context — colors, typography, logo, anti-patterns, voice rules — and generates on-brand content.
5. Go deeper (optional)
| Session | What it adds | Command |
|---------|-------------|---------|
| 1. Core Identity | Colors, fonts, logo, tokens | brand_start (done above) |
| 2. Visual Identity | Composition, anti-patterns, illustration style | brand_deepen_identity |
| 3. Messaging | Voice, tone, never-say words, brand story | brand_compile_messaging |
| 4. Content Strategy | Personas, journey stages, themes | brand_build_personas |
Each session enriches brand-runtime.json. Stop at any point — Session 1 alone is valuable.
6. Share with your team
> Run brand_brandcode_connect to save on Brandcode Studio
Your brand persists on brandcode.studio. Teammates pull the same brand into their tools. One source of truth.
---
What It Does
**Session 1: Core Identity** -- Extract colors, fonts, and logo from a website or Figma file. Compile into DTCG tokens, a structured design synthesis layer, a portable DESIGN.md, and an HTML report.
来源
awesome · https://github.com/Brand-System/brandsystem-mcp
按领域浏览
MCP 服务
Traction
15 ★
收录于
昨天

更多MCP 服务

查看MCP 服务全部 5,525 条 →

所属领域与标签

每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。

浏览全部领域 →

← 返回索引