What are the prerequisites to use Penpot MCP?
Python 3.12+, a Penpot account, and optionally Claude Desktop or Cursor IDE for AI integration.

@montevive
Basic information
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,
Add this server to your MCP-compatible client using the configuration below.
{
"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"
}
}
}
}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.
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.
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.
Python 3.12+, a Penpot account, and optionally Claude Desktop or Cursor IDE for AI integration.
Create a `.env` file with `PENPOT_API_URL`, `PENPOT_USERNAME`, and `PENPOT_PASSWORD` variables.
Tools include `list_projects`, `get_project_files`, `get_file`, `export_object`, `get_object_tree`, and `search_object`.
Add the MCP server configuration (command, args, env) to Claude Desktop’s config file (`claude_desktop_config.json`).
Yes, clone the repository, create a virtual environment, and install with `pip install -e .` or `uv sync`.
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MCP server that lets Claude Code, Cursor or Codex ask you for API keys on a local page and write them to .env. The agent only ever sees key names.

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