Recently, Figma officially launched its official Model Context Protocol (MCP) service, bringing a revolutionary breakthrough to AI-driven design-to-code workflows. This service significantly improves code generation efficiency and accuracy through smarter data transmission methods, attracting widespread attention in the industry. The AIbase editorial team has compiled the latest information to provide you with an in-depth analysis of the highlights and industry impact of Figma's MCP service.
Figma Official MCP Service: Seamless Integration Between Design and Development
Figma’s official MCP service went live in early June 2025, adopting the SEE model (simplify, enhance, efficiency), eliminating the cumbersome steps required for traditional MCP configuration and providing users with an out-of-the-box experience. Compared to third-party non-official MCP solutions, the official version can extract more detailed design information, including components, variables, styles, layer names, comments, and other metadata, even supporting high-level design screenshots and pseudocode descriptions of interaction behaviors. These rich data provide AI coding tools with more comprehensive context support, greatly enhancing the conversion efficiency from design to code.
AIbase learned that the Figma MCP service runs on local servers and integrates seamlessly with mainstream IDEs (such as VS Code, Cursor, Windsurf) and AI coding tools (such as GitHub Copilot, Claude Code). Users only need to enable the Dev Mode MCP server in the Figma desktop application preferences to achieve real-time data transmission between design and development, significantly reducing communication friction between designers and developers.
Core Highlights: More Precise and Efficient AI Code Generation
The greatest advantage of Figma's official MCP service lies in its fine-grained handling of design data. Through the following key features, MCP provides higher-quality input for AI coding tools:
Rich metadata support: MCP can extract metadata such as components, variables, and styles from Figma design files, reducing the burden on large language models (LLMs) during the search and reasoning process, thus generating more accurate code.
Overall structural insight: By providing high-level design screenshots, MCP helps LLMs understand the overall structure, flow logic, and responsive layout of the page, ensuring that the generated code is highly consistent with the design.
Interaction behavior description: MCP supports extracting pseudocode or actual code examples to describe defined interaction behaviors in the design, such as button clicks and page transitions, improving the dynamic functionality implementation of the code.
Content and logic extraction: Text, SVG, images, layer names, and comments in the design are fully extracted, helping AI tools better understand the interface data model and content filling logic.
AIbase testing found that these functions of the MCP service allow AI coding tools (such as Cursor, Copilot) to generate code closer to production environments when processing complex design files, reducing the amount of manual adjustments developers need to make.
Industry Response: Social Media Buzz and User Expectations
Since the launch of Figma's official MCP service, it has sparked a wave of discussion on social media. Many designers and developers have expressed that the release of the official MCP solves the problem of incomplete data extraction in non-official versions, injecting new vitality into AI-driven development processes. Compared to Figma's previously released Figma Make platform, the MCP service focuses more on structured output of design data and has stronger synergy with AI coding tools, making it particularly suitable for teams that need to quickly generate Web, Android, or iOS interfaces from design drafts.
However, some users have expressed expectations for the future development of MCP services. For example, Figma plans to introduce remote server functionality within the next few months and further deepen integration with code repositories, which will provide more flexible support for distributed teams and large projects. Additionally, some users hope that Figma will further optimize support for complex design systems, ensuring complete synchronization of component libraries and design specifications.
Industry Impact: Reshaping the Design-to-Code Workflow
The launch of Figma's official MCP service marks a new stage in the collaboration between design and development. AIbase believes that this service not only enhances the automation level of the design-to-code process but also provides more efficient tools for cross-functional team collaboration. Whether for independent developers, startups, or large enterprises, the MCP service enables faster product iterations and higher design consistency.
At the same time, the openness of Figma MCP injects momentum into the development of the AI ecosystem. As a standardized protocol, MCP is not limited to Figma's ecosystem and may be adopted by other design tools or AI platforms, forming a broader industry standard. This openness and compatibility could become the key driver for the future integration of design and development.
Future Outlook: A New Era of Creative AI
The release of Figma's official MCP service is another milestone in the integration of AI technology and creative industries. AIbase observes that as the MCP service matures, the design-to-code workflow will become more intelligent and automated. In the future, Figma may further lower development barriers through deeper AI integration and remote server support, empowering more creators to quickly convert their design concepts into reality.
