Use Cases & Scenarios
This guide shows real-world scenarios for using Figma Console MCP in your workflow.
Your situation: You want to feed your design system to an AI code generator (Lovable, v0, Replit, Cursor) so it builds with your actual tokens, components, and styles instead of generic defaults.
What to say:
"Use figma_get_design_system_kit to extract my full design system from file key abc123, then use those tokens and component specs to build a signup page"
What happens:
- AI calls
figma_get_design_system_kit — gets tokens, components, and styles in one call
- Receives visual specs (exact colors, padding, typography, layout) for each component
- Uses actual token values (light/dark modes) instead of hardcoded values
- Builds the page using your real design system variables
Variations:
- “Extract only my tokens and styles” →
include: ["tokens", "styles"]
- “Get my Button and Card components with images” →
componentIds: ["1:234", "5:678"] + includeImages: true
- “Just get an inventory of what’s in my design system” →
format: "compact"
Why use this instead of individual tools: One call replaces figma_get_variables + figma_get_component + figma_get_styles, keeps the AI context window clean, and includes visual specs that individual tools don’t provide.
Your situation: You need to extract all design variables from your Figma design system.
What to say:
"Get all design variables from https://figma.com/design/abc123 and export them as CSS custom properties"
What happens:
- AI extracts all variables using Figma API
- Formats them as CSS custom properties
- Provides organized, ready-to-use CSS code
Example output:
:root {
/* Colors */
--color-primary-default: #4375FF;
--color-primary-hover: #2563EB;
/* Spacing */
--spacing-xs: 4px;
--spacing-sm: 8px;
/* Typography */
--font-size-body: 16px;
--line-height-body: 24px;
}
Scenario 6: Generate Tailwind Config
Your situation: You want to sync your Figma variables to Tailwind CSS.
What to say:
"Get variables from https://figma.com/design/abc123 and export as Tailwind config"
What happens:
- AI extracts variables
- Converts to Tailwind format
- Provides
tailwind.config.js code
Scenario 7: Audit Design System Usage
Your situation: You want to see which components are using specific design tokens.
What to say:
"Get all variables from my design system and show me where each one is used"
What happens:
- AI extracts variables with enrichment enabled
- Shows usage analysis
- Lists which styles/components use each variable
🔧 Component Implementation
Scenario 8: Implement Component from Figma
Your situation: You need to implement a Tooltip component from your design file.
What to say:
"Get the Tooltip component from https://figma.com/design/abc123?node-id=695-313 and help me implement it in React"
What happens:
- AI fetches component data with visual reference image
- Extracts layout, styling, and property information
- Helps you implement with accurate spacing, colors, and behavior
AI will provide:
- Component image for visual reference
- Layout properties (padding, spacing, auto-layout)
- Color and typography specs
- Implementation guidance
Scenario 9: Get Component Specifications
Your situation: You just need the specs for a component, not implementation help.
What to say:
"Get visual reference and layout specs for the Button component at node-id=123:456"
What happens:
- AI renders component as high-res image
- Extracts layout measurements
- Lists color values and typography
- You implement it yourself with accurate specs
Scenario 10: Compare Multiple Component Variants
Your situation: You have a Button component with Primary, Secondary, and Tertiary variants.
What to say:
"Get component data for these three button variants: node-id=1:2, node-id=1:3, node-id=1:4. Show me the differences"
What happens:
- AI fetches all three variants
- Compares their properties
- Highlights what changes between variants (colors, borders, padding, etc.)
✏️ Design Creation (Local Mode & Cloud Mode)
These scenarios require the Desktop Bridge plugin. In Local Mode, the plugin connects via WebSocket. In Cloud Mode, say “connect to my Figma plugin” first to pair via the cloud relay — then all the same prompts work from web-based AI clients like Claude.ai, v0, Replit, and Lovable.
Scenario 11: Create Component Variants with Variables
Your situation: You want to create a complete button component set with multiple variants, sizes, and states—all bound to design system variables.
Prerequisites:
- Local mode with Desktop Bridge plugin running
- Design system variables defined (colors, spacing, radius)
What to say:
"Create a button component with:
- 4 types: primary, secondary, outline, ghost
- 3 sizes: small, medium, large
- 5 states: default, hover, active, focus, disabled
Bind the colors to my design system variables (piccolo for primary, beerus for secondary, etc.) and use the spacing/radius variables for padding and border-radius."
What happens:
- AI loads required fonts
- Creates individual component variants (60 total: 4×3×5)
- Applies variable bindings for colors, padding, and border-radius
- Combines into a component set
- Calls
figma_arrange_component_set to organize with labels and proper layout
- Takes a screenshot to verify the result
Follow-up prompts:
- “Add descriptions to each variant”
- “Adjust the hover states to use darker colors”
- “Create a similar set for icon buttons”
Scenario 12: Build a Design System from Scratch
Your situation: You’re starting a new project and need to set up design system foundations.
What to say:
"Create a design system with:
1. A color variable collection with:
- Primary colors (piccolo, beerus, goten)
- Neutral colors (bulma, trunks, goku)
- Semantic colors (success, warning, error)
2. A spacing variable collection with xs (4px) through 2xl (48px)
3. A radius variable collection with none, sm, md, lg, full
Then create a basic button component using these variables."
What happens:
- AI creates variable collections
- Adds variables with appropriate values
- Creates a button component bound to the variables
- Provides a screenshot of the result
Scenario 13: Organize Existing Component Set
Your situation: You have a messy component set that needs proper organization with labels.
What to say:
"Find my 'Button' component set on the current page and arrange it with:
- Proper variant labels
- Purple dashed border container
- Full-width frame"
What happens:
- AI finds the component set by name
- Calls
figma_arrange_component_set with your specifications
- Variants are organized in a grid with row/column labels
- Everything is wrapped in a properly styled container
Scenario 14: Create Component with Auto-Layout
Your situation: You need a card component with proper auto-layout settings.
What to say:
"Create a card component with:
- Vertical auto-layout, 16px gap
- 24px padding all around
- Rounded corners (12px)
- Contains: image placeholder, title text, description text, action button
- Bind padding to my spacing variables"
What happens:
- AI executes Plugin API code to create the frame
- Sets up auto-layout with specified settings
- Creates child elements (image, text, button)
- Binds padding to design system variables
- Converts to component
Scenario 15: Add Documentation to Components
Your situation: You want to add descriptions to your components for design system documentation.
What to say:
"Add a description to my Button component explaining:
- When to use each variant
- Accessibility requirements
- Usage guidelines
Use markdown formatting."
What happens:
- AI finds the Button component
- Calls
figma_set_description with markdown-formatted documentation
- Description appears in Figma’s component panel
Scenario 16: Clone and Modify Existing Design
Your situation: You want to create variations of an existing component.
What to say:
"Clone my 'Card/Default' component 3 times and modify each:
1. 'Card/Compact' - reduce padding to 12px
2. 'Card/Featured' - add a colored top border
3. 'Card/Minimal' - remove the image placeholder"
What happens:
- AI clones the component using
figma_clone_node
- Modifies each clone using node manipulation tools
- Renames using
figma_rename_node
- Takes a screenshot to show all variations
Scenario 17: Variable Mode Management (Local Mode & Cloud Mode)
Your situation: You need to add a dark mode to your design system variables. This works in both Local Mode and Cloud Mode (after pairing).
What to say:
"Add a 'Dark' mode to my colors collection and set up the dark mode values:
- piccolo: #60A5FA (lighter blue)
- beerus: #A78BFA (lighter purple)
- background: #1F2937 (dark gray)
- text: #F9FAFB (light gray)"
What happens:
- AI finds the colors collection
- Adds a new mode using
figma_add_mode
- Updates each variable with dark mode values using
figma_update_variable
- Confirms the changes
Follow-up prompts:
- “Show me all variables with their light and dark values”
- “Create a preview frame showing both modes”
Scenario 18: Batch Component Creation
Your situation: You need to create a set of icon buttons with consistent styling.
What to say:
"Create icon button components for these actions:
- Edit (pencil icon)
- Delete (trash icon)
- Copy (duplicate icon)
- Share (share icon)
Each should have 3 sizes (24px, 32px, 40px) and use the same variable bindings as my regular buttons."
What happens:
- AI creates each icon button variant
- Applies consistent styling and variable bindings
- Combines into a component set
- Organizes with
figma_arrange_component_set
- Takes a final screenshot
Scenario 19: Interactive Iteration Workflow
Your situation: You’re creating a component and want to refine it based on visual feedback.
What to say:
"Create a navigation bar component with a logo, menu items, and a CTA button. After each step, show me a screenshot so I can give feedback."
What happens:
- AI creates initial navigation structure → takes screenshot
- You provide feedback (“make the menu items larger”)
- AI modifies → takes screenshot
- Continue iterating until you’re satisfied
This workflow leverages the screenshot feedback loop for precise design control.
☁️ Cloud Mode Workflows
These scenarios are for web-based AI clients (Claude.ai, v0, Replit, Lovable) that connect to Figma through the cloud relay. No local installation required — just the Desktop Bridge plugin running in Figma.
Scenario: Connect Cloud AI to Figma (First Time)
Your situation: You’re using Claude.ai (or v0, Replit, Lovable) and want to create or modify designs in Figma.
What to say:
"Connect to my Figma plugin so we can start designing"
or
"Pair with my Figma file"
What happens:
- AI generates a 6-character pairing code (valid for 5 minutes)
- You enter the code in the Desktop Bridge plugin’s Cloud Mode section
- The plugin connects to the cloud relay — you’re paired
- All 93 Cloud Mode tools — including write/create tools — are now available through the cloud relay
Follow-up prompts:
- “Create a card component with an image, title, and description”
- “Update my primary color variable to #006699”
- “Show me what components are in this file”
Your situation: You’re using v0, Replit, or Lovable and want your actual design tokens — not REST API snapshots that require an Enterprise plan.
What to say:
"Connect to my Figma file and extract my design system variables"
What happens:
- AI generates a pairing code, you enter it in the plugin
- Plugin API extracts ALL variables on any Figma plan (Pro, Org, or Enterprise)
- AI receives full token data: colors, spacing, typography, with all mode values (Light/Dark/etc.)
- You can now generate code using your real design system
Why this matters: The Figma REST API requires an Enterprise plan to access variables. Cloud Relay bypasses this limitation because the Desktop Bridge plugin uses the Plugin API, which works on all plans.
Scenario: Update Design Tokens from Web Chat
Your situation: You’re in a meeting, using Claude.ai on a laptop, and want to update a brand color across your design system.
What to say:
"Connect to Figma and change the primary brand color to #006699 across all modes"
What happens:
- AI generates pairing code, you enter it in the Desktop Bridge plugin
- AI reads your current variables to find the primary color
- Updates the value across Light, Dark, and any other modes
- Confirms the changes with the new values
Scenario: Create Components from Web AI Client
Your situation: You’re using Claude.ai to prototype a new component and want it created directly in Figma.
What to say:
"Connect to my Figma and create a notification toast with an icon, title text, and a dismiss button"
What happens:
- AI generates pairing code, you enter it in the plugin
- AI uses the plugin API to create a frame with auto-layout
- Adds child elements (icon placeholder, title text, dismiss button)
- Takes a screenshot to verify the result and show you what was created
🔍 Visual Debugging Workflows
Scenario 20: Document Plugin State
Your situation: You want to show someone what your plugin looks like at a specific point.
What to say:
"Navigate to my plugin, take a full-page screenshot, and save it as 'plugin-error-state'"
What happens:
- AI takes full-page screenshot
- Saves with your custom filename
- You can share the visual state with your team
Scenario 21: Monitor Visual Changes
Your situation: Testing if plugin UI updates correctly.
What to say:
"Take a screenshot, then I'll make a change, then take another screenshot"
What happens:
- AI takes “before” screenshot
- You make your changes
- AI takes “after” screenshot
- You can compare the two states
🚀 Advanced Workflows
Scenario 22: Full Design System Export
Your situation: Migrating from Figma to code.
What to say:
"Extract everything from my design system:
1. Get all variables and export as CSS
2. Get all text styles and export as Tailwind
3. Get all color styles as Sass variables
4. List all components"
What happens:
- AI systematically extracts all design system data
- Provides multiple export formats
- Organizes everything for your codebase
Scenario 23: Plugin Development Sprint
Your situation: Rapid plugin development with continuous debugging.
Workflow:
1. "Watch console for 5 minutes while I develop"
→ AI monitors in background
2. "Show me any errors from the last 2 minutes"
→ AI filters recent error logs
3. "Take a screenshot of current state"
→ Visual checkpoint
4. "Reload the plugin and clear console"
→ Fresh start
5. Repeat...
Scenario 24: Design Token Migration
Your situation: Moving from Figma Styles to Variables.
What to say:
"Compare my old styles with new variables. Show me what changed and generate migration scripts"
What happens:
- AI gets both styles and variables
- Maps old → new
- Identifies breaking changes
- Suggests migration approach
💡 Tips for Effective Prompts
✅ Good Prompts
- Be specific: “Get the primary button component from https://figma.com/design/abc123?node-id=1:2”
- Include URL: Always provide your Figma file URL
- State intent: “…and help me implement it in React” (tells AI what you’ll do with the data)
- Request format: “export as CSS” vs “export as Tailwind”
❌ Avoid Vague Prompts
- ❌ “Get my design system” (which file?)
- ❌ “Help with my plugin” (what specifically?)
- ❌ “Show me components” (which ones? what data?)
🎯 Pro Tips
- Chain operations: “Navigate to X, watch console for 30s, then screenshot”
- Use filters: “Show me only error logs from the last minute”
- Be specific about formats: “Export as Tailwind v4 syntax”
- Request enrichment explicitly: “Get variables with CSS exports and usage information”
- Cloud Mode — connect first: Start by saying “pair with my Figma plugin” or “connect to Figma” before asking for design changes
- Use natural language: You don’t need to know tool names. Say “create a blue square” not “call figma_execute”
With Figma Official Dev Mode MCP
Workflow:
- Use Figma Dev Mode MCP to generate component code
- Use Figma Console MCP to get design token values
- Replace hardcoded values with tokens
- Use Console MCP to debug when integrated
Example:
// Step 1: Dev Mode MCP generates
<Button className="bg-[#4375ff]">Click me</Button>
// Step 2: Console MCP provides token
--color-primary: #4375FF
// Step 3: You refactor
<Button className="bg-primary">Click me</Button>
📚 More Examples
See also:
🐛 Plugin Development & Debugging
Limited availability. Console monitoring currently captures logs from the Desktop Bridge plugin sandbox only. Monitoring a separate plugin’s console is not supported — Figma allows only one plugin to run at a time, and each plugin has an isolated console. This was possible in earlier versions using Chrome DevTools Protocol (CDP) but is not compatible with the current WebSocket bridge architecture. We’re exploring workarounds and will update this section when a solution is available.
Scenario: Simple Plugin Debugging
Your situation: You’re developing a Figma plugin and want to see console output from the Desktop Bridge plugin itself.
What to say to your AI assistant:
"Check the last 20 console logs"
What happens:
- AI retrieves console logs from the Desktop Bridge plugin sandbox
- Shows errors, warnings, and log statements with timestamps
Follow-up prompts:
- “Show me just the error logs”
- “What does this stack trace mean?”
- “Help me fix this error”
Note: These console tools capture output from the Desktop Bridge plugin (code.js), not from other plugins running in Figma. To debug a separate plugin, you would need to use Figma’s built-in DevTools (Help → Debugging → Open DevTools) alongside the MCP tools.