AI app for it and development · no coding needed
Live design file agent access console
Reduce manual design-to-code copying while keeping design files and code aligned.
Made for: Product teams connecting AI agents and development tools to live design files
What it does for you
The problem
Agents and development tools cannot read or modify live design files, so design state and code drift apart and handoff stays manual.
What it gives you
Reviewed, source-linked design changes and code mappings
What you give it
Live design filescomponentvariable definitionsprototype source filesteam conventions
Build your own version of Figma MCP, Figma for Agents and more
One app with what these 3 AI tools do, yours to keep and change: Figma MCP, Figma for Agents, Design in Figma using Cursor Agent + MCP.
Everything these tools do, in one app
- Live design context access Makes current design state available outside the design app so external tools and agents can read components, layouts, and interaction details.Found in Figma MCP, Figma for Agents, Design in Figma using Cursor Agent + MCP
- Agent access to components Lets AI agents read and edit real Figma components, variables, and auto layout instead of inventing new assets.Found in Figma for Agents, Design in Figma using Cursor Agent + MCP
- Natural-language control Allows users to read and modify Figma designs programmatically using plain language commands.Found in Design in Figma using Cursor Agent + MCP
- Bidirectional code sync Propagates updates between code and Figma in real time so design and implementation stay aligned.Found in Design in Figma using Cursor Agent + MCP
- Design-to-code mapping Links design elements or node IDs to production code components to reduce guesswork during handoff.Found in Figma MCP, Figma for Agents
- Prototype source file support Lets tools inspect underlying code and behavior of prototypes rather than working only from static screenshots.Found in Figma MCP
- Design token sync and drift detection Reads variable definitions from Figma selections and detects when design tokens drift out of sync with code.Found in Figma for Agents
- Convention rules for agents Uses markdown-driven rules to teach agents a team's component and spacing conventions before they edit the canvas.Found in Figma for Agents
- Bulk and batch operations Updates text across many elements, applies component overrides, and manages annotations at scale.Found in Design in Figma using Cursor Agent + MCP
- Design manipulation and export Creates frames, rectangles, and text; clones, moves, and resizes nodes; adjusts layouts and colors; and exports images in multiple formats.Found in Design in Figma using Cursor Agent + MCP
- Automated accessibility output Generates screen reader and ARIA specs from real components to surface accessibility artifacts earlier.Found in Figma for Agents
- Parallel multi-agent workflows Supports running multiple agents in parallel for teams that split design and implementation responsibilities.Found in Figma for Agents
- Flexible deployment Allows deployment to cloud or local environments to suit different workflows and security needs.Found in Design in Figma using Cursor Agent + MCP
- Open source and extensible Provides MIT-licensed open source code and a broad set of MCP tools for wide Figma API coverage.Found in Design in Figma using Cursor Agent + MCP
- Design context portability Makes design information portable and machine-readable to reduce manual copying of specs and assets.Found in Figma MCP
How it works, step by step
- Read live design state, components, layouts and interaction details
- Let agents read and edit real components, variables and auto layout
- Accept plain-language commands to read and modify designs
- Propagate updates between code and design files in real time
- Link design elements or node IDs to production code components
- Inspect prototype source files and behavior
- Read variable definitions and detect design token drift
- Apply markdown convention rules before agents edit the canvas
- Run bulk text, override and annotation operations
- Create frames, rectangles and text; clone, move and resize nodes
- Adjust layouts and colors and export images in multiple formats
- Generate screen reader and ARIA specs from real components
- Run multiple agents in parallel across design and implementation work
- Deploy to cloud or local environments
- Expose an open, extensible tool set over the design API
- Export a versioned reviewed design change set with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Live design file agent access console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Live design file agent access console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce manual design-to-code copying while keeping design files and code aligned. For product teams connecting AI agents and development tools to live design files, convert live design state, component and variable definitions, prototype source files and team conventions into reviewed, source-linked design changes and code mappings. The benefit is a testable hypothesis, measured through accepted design changes per review hour and drift incidents after sync; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect live design files, component and variable definitions, prototype source files and team conventions, then follow this sequence: 1. Read live design state, components, layouts and interaction details. 2. Let agents read and edit real components, variables and auto layout. 3. Accept plain-language commands to read and modify designs. Resolve uncertain cases with qualified reviewers, approve reviewed, source-linked design changes and code mappings, and measure accepted design changes per review hour and drift incidents after sync against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One connected design workspace and one code repository; final design and code approval remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve design intent, source attribution, component accuracy and usage permissions. Design and code owners approve substantive changes and release scope. One connected design workspace and one code repository; final design and code approval remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One connected design workspace and one code repository; final design and code approval remain human. Implement one approved input format, a bounded representative case set and the first two task modules: read live design state, components, layouts and interaction details; let agents read and edit real components, variables and auto layout. Support the third module with operator review: accept plain-language commands to read and modify designs. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Design workspace APIs, code repositories, CI pipelines and issue trackers. Cloud or local deployment targets, asset storage and export destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Connection and permissions, Live design context, Agent run console, Review and approval, Sync and drift report. Use a project list, a central canvas view of the live design state, and a right-hand panel for agent runs, rules and comments. Let users compare design and code versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant node. Make the task-specific outcome reviewed, source-linked design changes and code mappings visible beside its evidence, review state and value baseline.
