Penpot MCP Server

@montevive

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基本信息

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开发工具

传输方式

stdio

作者

montevive

提交者

JM Robles

关于 Penpot MCP Server

Penpot MCP is a revolutionary Model Context Protocol (MCP) server that bridges the gap between AI language models and Penpot, the open-source design and prototyping platform. This integration enables AI assistants like Claude (in both Claude Desktop and Cursor IDE) to understand,

#penpot#design2code#code #ui #ux

Penpot MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "penpot": {
      "command": "uvx",
      "args": [
        "penpot-mcp"
      ],
      "env": {
        "PENPOT_API_URL": "https://design.penpot.app/api",
        "PENPOT_USERNAME": "your_penpot_username",
        "PENPOT_PASSWORD": "your_penpot_password"
      }
    }
  }
}

Penpot MCP Server 工具

Retrieve a list of all available Penpot projects.

Get all files contained within a specific Penpot project. Args: project_id: The ID of the Penpot project

Retrieve a Penpot file by its ID and cache it. Don't use this tool for code generation, use 'get_object_tree' instead. Args: file_id: The ID of the Penpot file

Export a Penpot design object as an image. Args: file_id: The ID of the Penpot file page_id: The ID of the page containing the object object_id: The ID of the object to export export_type: Image format (png, svg, etc.) scale: Scale factor for the exported image

Get the object tree structure for a Penpot object ("tree" field) with rendered screenshot image of the object ("image.mcp_uri" field). Args: file_id: The ID of the Penpot file object_id: The ID of the object to retrieve fields: Specific fields to include in the tree (call "penpot_tree_schema" resource/tool for available fields) depth: How deep to traverse the object tree (-1 for full depth) format: Output format ('json' or 'yaml')

Search for objects within a Penpot file by name. Args: file_id: The ID of the Penpot file to search in query: Search string (supports regex patterns)

Provide the Penpot API schema as JSON.

Provide the Penpot object tree schema as JSON.

Return a rendered component image by its ID.

List all files currently stored in the cache.

概览

What is Penpot MCP?

Penpot MCP is a Model Context Protocol (MCP) server that connects AI language models (like Claude) with the Penpot open-source design and prototyping platform. It enables AI-powered design analysis, automation, and natural language interaction with Penpot files.

How to use Penpot MCP?

Install via pip install penpot-mcp or uvx penpot-mcp, then run penpot-mcp or uv run penpot-mcp. Configure a .env file with Penpot API credentials (PENPOT_API_URL, PENPOT_USERNAME, PENPOT_PASSWORD). Integrate with Claude Desktop or Cursor IDE by adding the server’s MCP configuration.

Key features of Penpot MCP

Full MCP protocol compliance
Direct real-time access to Penpot API
AI-powered design component analysis
Automated export of assets in multiple formats
Design system compliance validation
Native Claude Desktop and Cursor IDE integration

Use cases of Penpot MCP

Automate design reviews with instant AI feedback on accessibility and usability
Generate documentation for design systems automatically
Check brand guideline compliance across projects
Bridge design-to-code workflows with AI assistance
Track design system adoption and component usage analytics

常见问题

What are the prerequisites to use Penpot MCP?

Python 3.12+, a Penpot account, and optionally Claude Desktop or Cursor IDE for AI integration.

Where do I put my Penpot credentials?

Create a `.env` file with `PENPOT_API_URL`, `PENPOT_USERNAME`, and `PENPOT_PASSWORD` variables.

What MCP tools are available?

Tools include `list_projects`, `get_project_files`, `get_file`, `export_object`, `get_object_tree`, and `search_object`.

How do I integrate with Claude Desktop?

Add the MCP server configuration (command, args, env) to Claude Desktop’s config file (`claude_desktop_config.json`).

Can I run the server locally from source?

Yes, clone the repository, create a virtual environment, and install with `pip install -e .` or `uv sync`.

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