Penpot MCP Server

Penpot MCP is a Model Context Protocol server that acts as an intelligent bridge between large language models—such as Claude—and the open‑source design platform Penpot. By exposing a full MCP implementation, the server allows AI assistants to ingest, analyze, and manipulate design files in real time. This solves a key pain point for teams that rely on AI to augment creative workflows: the lack of native, programmatic access to design assets. With Penpot MCP, developers can now feed entire design systems, component libraries, and project artifacts directly into the AI’s context, enabling richer, more accurate responses that reflect the current state of a design.

The server offers several core capabilities that translate into tangible productivity gains. First, it pulls live data from Penpot’s API, giving AI models up‑to‑date views of pages, components, and style guides. Second, it performs automated analysis—checking for accessibility violations, brand consistency, or layout anomalies—and returns actionable insights. Third, it supports export automation, allowing designers to trigger asset exports in multiple formats (SVG, PNG, Figma‑compatible JSON) through simple AI commands. These features collectively turn the design tool into a dynamic knowledge base that an assistant can interrogate, modify, and evolve.

For developers, Penpot MCP provides a versatile integration layer. The server exposes REST endpoints that can be called from any programming language, and it ships with a Python SDK for rapid prototyping. CLI utilities let teams run batch analyses or generate documentation without writing code, while the plugin architecture invites custom workflows—such as generating visual regression tests or syncing design tokens to a front‑end framework. Because the server follows MCP standards, it works seamlessly with any MCP‑compatible assistant, including Claude Desktop and Cursor IDE, giving teams flexibility in their toolchain.

Real‑world use cases illustrate the server’s value. Designers can ask an AI to review a new mockup for accessibility compliance, receive suggestions for color contrast improvements, and automatically tag components with semantic labels—all within a single conversation. Developers can pull design tokens into their codebase, generate component stubs from AI‑interpreted layouts, or create visual regression test suites that compare rendered UI against the latest design. In both scenarios, the AI gains context from the actual design files rather than relying on static screenshots or hand‑written descriptions, leading to higher accuracy and faster iteration.

In summary, Penpot MCP turns a design platform into an AI‑ready resource. By providing real‑time access, automated validation, and export capabilities within the MCP framework, it empowers teams to embed design intelligence directly into their workflows. Whether you’re refining UI/UX, maintaining brand consistency, or bridging the gap between design and code, Penpot MCP delivers a scalable, protocol‑compliant solution that unlocks the full potential of AI assistants in creative environments.