Design System MCPs: Giving Agents Real Design Context
Event details
Join us live to ask your questions
What you'll learn
What a design system MCP actually is, why it beats a design.md on its own, what it takes to stand one up, and where it still falls short. The short version: an MCP server resolves your tokens to real values and hands agents your actual component APIs, so they stop guessing and start asking. You'll leave knowing how to give your agents that context, on the design side and the engineering side.
The most valuable part of the discussion is the questions you ask. We're here to help.
Download our AI-Ready Design System Checklist
Agenda
1. What an MCP actually is
A plain definition, and what a server does when an agent asks it a question
2. Why your design system wants one
Drift used to accumulate at human speed. AI-assisted work generates it at machine speed.
3. MCP versus the alternatives
Where a design.md, a docs bot, or an off-the-shelf Figma MCP runs out of road. A generic server knows Figma's API. It doesn't know your tokens, your component APIs, or your standards.
4. Standing one up
Resolving tokens to real values, returning component APIs with their props, variants, and composition rules, and holding the line on naming and accessibility
5. Beyond the server
Tools, prompts, resources, and hooks, and what each one is good for
6. How the pieces fit
Tokens and primitives at the base, design.md, patterns, and linters in the middle, agents.md and your usage guidelines on top, and where the MCP sits among them
7. Mapping Figma to code
Pointing at a frame and getting the right component back, resolved through your library structure instead of guessed from pixels
8. What it solves, and what it doesn't
Honest limits, including where today's design agents still miss your components
9. Beyond product UI
Slide decks, email templates, and the other surfaces your design system should reach
10. Q&A
Who this is for
You'll get the most out of this if some of these look familiar: teams routing around the design system because raw AI feels faster, implementations that drift apart across products and platforms, Figma and code that no longer agree on components or naming, or AI output that looks close enough but doesn't hold the brand.
The session assumes you already have a design system in Figma with components running in production, and engineers who are using AI coding tools or about to be. If you're still building the system itself, the reading below is the better starting point.
Read this first
If you want context before the session starts, read design systems for AI agents for the design.md side of this, and the 5 levels of an AI-ready design system to place your own system. Knowing where you're starting from makes the walkthrough a lot more useful.
Book a design system deep dive
The presentation covers the principles. A call covers your system.
In 30 minutes we'll dig into the specific challenges you're hitting, share any advice we have, and figure out where we can help. We've worked with crews starting from zero and enterprises rebuilding systems that were never going to scale.
Bring whatever you've got. We'll tell you what we'd do first.
Presenters
Join us live to ask your questions
Design System MCPs: Giving Agents Real Design Context
Watch the recording
What you'll learn
What a design system MCP actually is, why it beats a design.md on its own, what it takes to stand one up, and where it still falls short. The short version: an MCP server resolves your tokens to real values and hands agents your actual component APIs, so they stop guessing and start asking. You'll leave knowing how to give your agents that context, on the design side and the engineering side.
The most valuable part of the discussion is the questions you ask. We're here to help.
Download our AI-Ready Design System Checklist
Agenda
1. What an MCP actually is
A plain definition, and what a server does when an agent asks it a question
2. Why your design system wants one
Drift used to accumulate at human speed. AI-assisted work generates it at machine speed.
3. MCP versus the alternatives
Where a design.md, a docs bot, or an off-the-shelf Figma MCP runs out of road. A generic server knows Figma's API. It doesn't know your tokens, your component APIs, or your standards.
4. Standing one up
Resolving tokens to real values, returning component APIs with their props, variants, and composition rules, and holding the line on naming and accessibility
5. Beyond the server
Tools, prompts, resources, and hooks, and what each one is good for
6. How the pieces fit
Tokens and primitives at the base, design.md, patterns, and linters in the middle, agents.md and your usage guidelines on top, and where the MCP sits among them
7. Mapping Figma to code
Pointing at a frame and getting the right component back, resolved through your library structure instead of guessed from pixels
8. What it solves, and what it doesn't
Honest limits, including where today's design agents still miss your components
9. Beyond product UI
Slide decks, email templates, and the other surfaces your design system should reach
10. Q&A
Who this is for
You'll get the most out of this if some of these look familiar: teams routing around the design system because raw AI feels faster, implementations that drift apart across products and platforms, Figma and code that no longer agree on components or naming, or AI output that looks close enough but doesn't hold the brand.
The session assumes you already have a design system in Figma with components running in production, and engineers who are using AI coding tools or about to be. If you're still building the system itself, the reading below is the better starting point.
Read this first
If you want context before the session starts, read design systems for AI agents for the design.md side of this, and the 5 levels of an AI-ready design system to place your own system. Knowing where you're starting from makes the walkthrough a lot more useful.
Book a design system deep dive
The presentation covers the principles. A call covers your system.
In 30 minutes we'll dig into the specific challenges you're hitting, share any advice we have, and figure out where we can help. We've worked with crews starting from zero and enterprises rebuilding systems that were never going to scale.
Bring whatever you've got. We'll tell you what we'd do first.
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