What are the prerequisites to use Penpot MCP?
Python 3.12+, a Penpot account, and optionally Claude Desktop or Cursor IDE for AI integration.
Penpot MCP Server
@montevive
基本信息
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 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
10Retrieve 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
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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