"Imagine that your Penpot file contains a full icon set in addition to the design itself, which uses some but not all of those icons. If you were to ask an AI such as Claude or Gemini to export only the icons that are being used, it wouldn't be able to do that. It's not able to interact with Penpot files."
"However, a Penpot MCP server can. It can perform a handpicked number of operations under set rules and permissions, especially since Penpot has an extensive API and even more so because it's open-source. The AI's job is simply to understand your intent, choose the right operation for the MCP server to perform (an export in this case), and pass along any parameters (i.e., icons that are being used). The MCP server then translates this into a structured API request and executes it."
Penpot MCP servers enable external AI to perform defined operations on Penpot design files by translating user intent into structured API requests. They act as a secure bridge that enforces rules and permissions so third-party LLMs do not access raw Penpot data directly. The AI determines intent, selects the appropriate operation (for example, exporting only icons in use), and provides parameters for the MCP server. The MCP server constructs and executes API calls against Penpot's open-source API. Because Penpot represents designs as code, designs can be programmatically created, edited, and analyzed at a granular, contextual level, enabling more powerful workflows and community-shaped integrations.
Read at Smashing Magazine
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