@brandsystem/mcp

Make your brand machine-readable. Extract identity from any website, structure it as tokens and policies, and make it available to every AI tool you use.

What It Solves

AI tools produce generic 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.

This MCP server extracts brand identity from live sources (websites, rendered pages, Figma files), compiles it into structured design tokens, runtime contracts, and interaction policies, and makes it available to any AI tool through the Model Context Protocol. The result is a .brand/ directory with your colors, fonts, logos, voice rules, visual anti-patterns, and DTCG tokens. Portable, version-controlled, and ready for any AI tool to consume.

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:

{
  "mcpServers": {
    "brandsystem": {
      "command": "npx",
      "args": ["-y", "@brandsystem/mcp"]
    }
  }
}

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

.brand/
  brand.config.yaml          ← brand name, source URLs, session state
  core-identity.yaml         ← colors (with roles), fonts, logo specs
  tokens.json                ← DTCG design tokens
  brand-runtime.json         ← single-file brand context for any AI agent
  interaction-policy.json    ← anti-patterns, voice constraints, never-say words
  design-synthesis.json      ← spacing, radius, shadows, component signals
  DESIGN.md                  ← portable design brief (agent-readable)
  brand-report.html          ← visual report (paste into any AI chat)
  assets/logo/               ← extracted logo files (SVG/PNG)

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)

... View full README on GitHub