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Penpot Better MCP

Penpot Better MCP

by Ti-wb

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    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to programmatically access self-hosted Penpot instances to read, create, modify, and export design elements through natural language. It provides 66 tools for managing projects, shapes, design tokens, and comments using a dual-access strategy of direct database reads and RPC API writes.
      12
      Apache 2.0
    • A
      license
      C
      quality
      D
      maintenance
      Enables AI assistants to create, modify, and manage Penpot designs programmatically, providing full manipulation capabilities for the open-source design tool.
      81
      52 npm
      20
      MIT
    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables interaction with Penpot, the open-source design platform, through tools for managing projects, files, components, design tokens, exports, comments, teams, and more.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to write AI-generated designs into design-tool canvases (MasterGo, Penpot) as native editable layers, and to read canvas selections back out as HTML + Tailwind, design tokens, and SVG assets. Runs locally with progressive tool disclosure and structurally truncated results so large design files stay within an agent's context budget.
      Apache 2.0
    • A
      license
      A
      quality
      B
      maintenance
      Enables an agent to read, edit, and build Figma designs from scratch — including style guides, variables, components, and screens — through a local plugin bridge to the open file's Plugin API, with no Figma token or REST API calls.
      21
      26 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables an AI agent to read and write a product's design screens on a shared, versioned canvas: creating and editing HTML screens and shared parts, taking screenshots, linking flows, posting comments and annotations, and opening or approving proposals. Every drawing is returned with its screenshot so the agent can see what it produced, letting screens persist and evolve across chats instead of starting from zero.
      1
      MIT