Figma Make vs Marmo UI

Figma Make turns natural-language prompts into interactive wireframes, flows, dashboards and apps. A project can start from scratch or from a frame or component brought in from Figma Design. Users can refine generated work in a visual editor, adjust code in a built-in editor or prompt again. It can create interactive, data-connected prototypes that users can refine and test, using real content or API data through a backend integration. Prototypes can be shared with a team or published publicly. Prompts use AI credits, and the amount depends on the model, task complexity and context volume. Organization and Enterprise members can use vetted partner connectors such as Notion, Asana, Linear, GitHub and Atlassian; Organization members can also connect custom MCP servers subject to organization settings. Figma Make is listed for macOS and web. Its closed beta for using Make in a local codebase is Mac-only and requires the Figma Beta desktop app for Mac. A Professional Full seat is listed at $16 a month, billed monthly, with 3,000 AI credits per month.

Marmo UI pairs an open-source React design system with a hosted MCP server to help AI agents compose dashboards and apps using named @marmoui/ui components. The server provides live component APIs, composition patterns and generation rules; generated files pass through a review step that checks imports, props and compositions. The library includes more than 50 production-ready components and comes with Storybook and a Figma library. Developers install the React package with npm. The free plan includes documentation, the design tools and MIT-licensed core components, and allows unlimited projects, commercial use and no rate limits. Pro adds generation guided by a DESIGN.md file with brand details, plus composition patterns, Pro blocks, a hosted design-system site and priority support. It costs $9.99 per month, and a 14-day trial is listed. Integration instructions cover Claude Code, Codex, Cursor, Gemini CLI, Windsurf and other MCP clients. Generated code belongs to the user, uses the user’s own LLM tokens and stays in the user’s repository; it does not phone home.