systembridge-mcp
Enables extraction of design tokens from Figma variables, validation of Figma tokens against the design system, and generation of component documentation.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@systembridge-mcpAudit my design tokens for accessibility issues."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
systembridge-mcp: MCP Server for Design Systems
An AI-native Model Context Protocol (MCP) server that gives LLMs and agents deep knowledge of design systems and design tokens, enabling intelligent design system evolution, token analysis, and designer-to-developer handoffs.
What is this?
systembridge-mcp teaches AI assistants (like Claude, GPT, or custom agents) how to work with your design system. Instead of just answering questions about design, the AI can:
Understand your design tokens: browse, search, and explain color palettes, spacing scales, and typography
Plan new features: describe what you need ("a login page"), get components and tokens required
Audit designs before handoff: check if your design has all the tokens it needs, find gaps, verify accessibility
Match colors and components: upload a screenshot or describe UI, get back what matches your system
Generate and validate tokens: create palettes, check WCAG contrast, scaffold semantic tokens
Evolve your system: transform tokens, migrate naming, manage themes and brands
Designers: Think of it as a design system assistant that knows your token library. Ask "what red for error states?" or "what tokens should I apply on this mockup?" — no code required.
Developers: A programmatic interface to design tokens with AI-native tooling for analysis, transformation, and code generation.
Related MCP server: tokensStudioMCP
Quick Start
What you need: Node.js 18+ and an AI assistant that supports MCP (e.g. Claude Desktop, Cursor).
Install in your design-token project:
npm install -D systembridge-mcpAdd a config file in your project root (optional; sensible defaults apply):
// .systembridge-mcp.json or systembridge-mcp.config.json { "tokenPaths": ["tokens/**/*.json", "design-tokens/**/*.json"] }Add to your MCP config (e.g.
.cursor/mcp.jsonfor Cursor):{ "mcpServers": { "systembridge-mcp": { "command": "npx", "args": ["systembridge-mcp"] } } }Restart your AI assistant. Look for the MCP icon — you should see 32 tools from systembridge-mcp. No path configuration needed when using project-level config.
Next: Getting Started | Setup by Client (Cursor, VS Code, Claude) | Agent Instructions (optional AI guidance).
For local development: TESTING.
Example Conversations
For Designers
"I need to design a dashboard with data tables and stat cards. What components and tokens do I need?"
The AI uses plan_flow to identify UI patterns, list required components, and tell you what token slots to fill.
"I'm using button, text-input, card, and modal. Does my design system cover everything?"
The AI uses audit_design to check for missing tokens, naming issues, and accessibility problems.
"I see a UI with colors #3B82F6, #EF4444, #F3F4F6. Which tokens match?"
The AI uses analyze_ui with perceptual color matching to find the closest tokens.
For Developers
"Generate a brand color palette with hue 220, chroma 0.7, and map it to semantic tokens for light mode."
The AI uses generate_palette + map_palette_to_semantics + check_contrast to create accessible tokens.
"Run a full audit of my design tokens. Check naming, accessibility, and coverage."
The AI uses audit_semantics + analyze_coverage + check_contrast to produce a health report.
"I have legacy tokens that don't follow our naming convention. Help me migrate them safely."
The AI uses analyze_topology → generate_refactor_scenarios → execute_migration to plan and execute the migration.
Features
Area | Tools |
Designer intelligence |
|
Token management |
|
Semantic tokens |
|
Color & accessibility |
|
Themes & brands |
|
Scales |
|
Migration |
|
Figma |
|
7 pre-built prompts orchestrate multiple tools: create-token, audit-tokens, design-semantic-tokens, design-color-palette, design-from-scratch, design-handoff-review, component-reference.
Full reference: docs/features.md
Documentation
Guide | Description |
Full installation, config options, troubleshooting | |
Per-client setup (Cursor, VS Code, Claude Desktop, Claude Code) | |
Optional AI usage guidance and rule templates | |
Test with | |
Designer workflow, example prompts, no-code usage | |
CLI, MCP API, extending the server, tests, benchmarks | |
Full feature and tool reference | |
Config file, env vars, token paths | |
Risk assessment and scenario generation | |
Execution, validation, and rollback | |
Figma variable sync and validation | |
Architecture guide for LLMs and agents |
Contributing
Contributions welcome. Fork, create a feature branch, make your changes, run npm run build, and submit a pull request.
See docs/AGENT_HANDOFF.md for codebase architecture.
License
MIT — see LICENSE. Copyright © 2024–2026 Tasos Dervenagas.
Acknowledgments
Built on Model Context Protocol, Style Dictionary, Leonardo, and WCAG 2.1. Inspired by W3C DTCG, Tokens Studio, and design systems from Primer, Polaris, and Carbon.
Support: GitHub Issues · GitHub Discussions · MCP Discord
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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