penpot-mcp-server
MCP server for self-hosted Penpot — AI-powered UI/UX design and prototyping (66 tools)
Install / Use
claude mcp add ancrz -- npx -y github:ancrz/penpot-mcp-serverIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
DesignSupported Platforms
Skill content
View source on GitHubPenpot MCP Server
AI-powered design tool access for self-hosted Penpot via Model Context Protocol.
What is this?
An MCP server that gives AI agents (like Claude Code, Cursor, or any MCP-compatible client) full programmatic access to your self-hosted Penpot instance. AI can read, create, modify, and export design elements — from rectangles and text to full UI components — all through natural language.
Think of it as the bridge between your AI assistant and your design tool.
Problems it solves
| Problem | Solution | |---|---| | Manual design work | AI creates UI components, layouts, and prototypes directly in Penpot | | No programmatic API for Penpot | 68 tools covering projects, shapes, text, exports, comments, and more | | Design-to-code gap | Generate CSS from any shape, export to SVG/PNG, extract design tokens | | Repetitive tasks | Batch operations — rename shapes, update colors, create variants | | Design system maintenance | Read/write components, colors, typographies programmatically |
Architecture
graph TB
AI["AI Agent\n(Claude Code · Cursor · Gemini CLI)"]
subgraph SERVERS["MCP Layer"]
MCP["penpot-mcp — Python\n68 tools · :8787\nDB reads + API writes + Plugin"]
OMCP["Penpot MCP — Official\n~20 tools · penpot/penpot monorepo\nPlugin API only · TypeScript"]
end
subgraph PENPOT["Penpot Stack (Docker)"]
PG["PostgreSQL\n:5432"]
BE["Backend\n:6060"]
FE["Frontend\n:9001"]
EX["Exporter\n:6061"]
end
subgraph BRIDGE["Browser Plugin Bridge"]
WS["WebSocket Server\n:4402"]
UI["ui.html\niframe · full browser API"]
PJ["plugin.js\nworker sandbox · penpot.*"]
end
AI -->|"Streamable HTTP :8787"| MCP
AI -->|"Streamable HTTP"| OMCP
MCP -->|"asyncpg · direct SQL"| PG
MCP -->|"httpx · RPC API"| BE
MCP -->|"PNG / SVG export"| EX
MCP <-->|"WebSocket"| WS
OMCP <-->|"WebSocket :4402"| WS
WS <-->|"ws://localhost:4402"| UI
UI <-->|"postMessage"| PJ
PJ -->|"penpot.* API"| FE
FE -.->|"proxy"| BE
BE --> EX
style AI fill:#7c3aed,color:#fff
style MCP fill:#2563eb,color:#fff
style OMCP fill:#0f766e,color:#fff
style PG fill:#16a34a,color:#fff
style BE fill:#ea580c,color:#fff
style FE fill:#ea580c,color:#fff
style EX fill:#ea580c,color:#fff
style WS fill:#0891b2,color:#fff
style UI fill:#0891b2,color:#fff
style PJ fill:#0891b2,color:#fff
Tri-layer access strategy:
- Reads go directly to PostgreSQL via
asyncpg— fast and reliable, bypasses API overhead - Writes go through Penpot's RPC API via
httpx— ensures proper change tracking and undo history - Exports use Penpot's built-in exporter (headless Chromium) for pixel-perfect SVG/PNG output
- Live canvas goes through the Browser Plugin bridge (port 4402) — shared architecture with the official Penpot MCP, enabling both servers to coexist and complement each other in the same AI workflow
Tech Stack
| Component | Technology | Purpose | |---|---|---| | Language | Python 3.13 | Runtime | | MCP SDK | FastMCP | Protocol handling, tool registration | | Database | asyncpg | Direct PostgreSQL access | | HTTP Client | httpx | Penpot RPC API calls | | Validation | Pydantic v2 | Automatic parameter validation | | Package Manager | uv | Fast Python dependency management | | WebSocket | websockets | Real-time browser plugin bridge | | Container | Docker | Deployment alongside Penpot |
Quick Start
Prerequisites
- Self-hosted Penpot running via Docker Compose (official guide)
- Docker and Docker Compose v2 installed
- Access tokens enabled in your Penpot instance (see Enable Access Tokens)
Option A: Automated Setup
git clone https://github.com/ancrz/penpot-mcp-server.git
cd penpot-mcp-server
chmod +x setup.sh
./setup.sh
The script will guide you through configuration, build the Docker image, and start the server.
Option B: Manual Setup
1. Clone the repository
git clone https://github.com/ancrz/penpot-mcp-server.git
cd penpot-mcp-server
2. Create your configuration
cp .env.example .env
Edit .env with your Penpot details:
# Your Penpot access token (see "Enable Access Tokens" below)
PENPOT_ACCESS_TOKEN=your-token-here
# Your Penpot database password (from your Penpot docker-compose.yml)
PENPOT_DB_PASS=your-db-password
# Public URL where you access Penpot in the browser
PENPOT_PUBLIC_URL=http://localhost:9001
3. Add the MCP service to your Penpot Docker stack
Add the penpot-mcp service definition to your existing Penpot docker-compose.yml. See docker-compose.penpot.yml for the complete service definition to copy.
4. Build and start
docker compose up -d --build penpot-mcp
5. Verify it's running
# Quick health check
curl -s http://localhost:8787/
# → {"service": "Penpot MCP", "status": "ok", "version": "0.1.0"}
# Full MCP protocol initialization
curl -s http://localhost:8787/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'
You should see a JSON response with the server capabilities.
Connect Your AI Agent
Penpot MCP uses network transport (streamable HTTP) — the server runs as a Docker container and clients connect via HTTP. This means:
- The server is always running independently (via Docker Compose)
- The client only needs the URL to connect — no process spawning
envin the client's JSON config is irrelevant — credentials live in the server's own.envfile (configured during setup)- Any client on the same machine (or network) can connect to
http://localhost:8787/mcp
Key difference from stdio servers: With stdio servers (like Skill Swarm), the client launches the process and injects env vars. With network servers like Penpot MCP, the server manages its own credentials. The
envblock in your client's MCP config has no effect.
Claude Code
Claude Code uses "type": "http" for streamable HTTP connections.
Global (~/.claude.json):
{
"mcpServers": {
"penpot": {
"type": "http",
"url": "http://localhost:8787/mcp"
}
}
}
Project-level (.mcp.json in your project root):
{
"mcpServers": {
"penpot": {
"type": "http",
"url": "http://localhost:8787/mcp"
}
}
}
Restart Claude Code. You should see 68 tools from the penpot server listed when you run /mcp.
Note: Use
"type": "http", not"streamable-http". Claude Code mapshttpto the streamable HTTP transport internally. Usingstreamable-httpwill cause a schema validation error.
Gemini CLI
Gemini CLI uses httpUrl (not url) for streamable HTTP connections. Transport is inferred from the field name.
Config file: ~/.gemini/settings.json
{
"mcpServers": {
"penpot": {
"httpUrl": "http://localhost:8787/mcp"
}
}
}
Note: Gemini CLI distinguishes between
url(SSE transport) andhttpUrl(streamable HTTP transport). Penpot MCP uses streamable HTTP, so usehttpUrl. Notypefield needed.
Antigravity
Antigravity uses serverUrl for HTTP-based MCP servers.
Config file: ~/.gemini/antigravity/mcp_config.json
{
"mcpServers": {
"penpot": {
"serverUrl": "http://localhost:8787/mcp"
}
}
}
Note: Antigravity uses
serverUrl(noturlorhttpUrl). If Antigravity runs inside Docker, make sure it can reachlocalhost:8787on the host — you may needhost.docker.internal:8787instead oflocalhost:8787depending on your Docker network setup.
Quick Comparison
| | Claude Code | Gemini CLI | Antigravity |
|---|---|---|---|
| Config file | ~/.claude.json or .mcp.json | ~/.gemini/settings.json | ~/.gemini/antigravity/mcp_config.json |
| URL field | "url" | "httpUrl" | "serverUrl" |
| Type field | "type": "http" (required) | Not needed (inferred) | Not needed (inferred) |
| env in JSON | No effect (network server) | No effect (network server) | No effect (network server) |
| Credentials | Server's .env file | Server's .env file | Server's .env file |
| Docker networking | localhost:8787 | localhost:8787 | May need host.docker.internal:8787 |
Example prompts
Once connected, you can ask your AI agent things like:
- "List my Penpot projects"
- "Create a login form with email/password fields and a submit button"
- "Export the Login Card frame as SVG"
- "What colors are defined in the design system?"
- "Add a comment at position (100, 200) saying 'Review this layout'"
Interactive Mode: Browser Plugin
The Penpot MCP Plugin bridges the AI agent with the live Penpot canvas, enabling real-time context awareness:
- Live selection: AI can query which shapes you currently have selected
- Script execution: AI can run JavaScript directly via the Penpot Plugin API
These features require the browser plugin to be connected. The 66 headless tools work without it.
Loading the Plugin
- Make sure the MCP server is running:
docker compose up -d penpot-mcp - Open Penpot in your browser
- Press Ctrl+Alt+P (or Main Menu -> Plugin Manager)
- Paste the URL in the input field:
http://localhost:8787/plugin/manifest.json - Click Install → Allow on the permissions dialog
- Click Open to launch the plugin panel
The plugin panel appears on the right. When the status indicator turns green, the AI agent has live access to the canvas.
Penpot Flags Requirement
The Penpot backend must have enable-plugins-runtime in PENPOT_FLAGS:
PENPOT_FLAGS=enable-login-with-password enable-registration enable-access-tokens enable-plugins-runtime
Restart required: After adding
enable-plugins-runtime, restart bothpenpot-backendandpenpot-frontend:docker compose restart penpot-backend penpot-frontend
Browser Compatibility
| Browser | Status | Notes | |---------|--------|-------| | Firefox | Works out of the box | No local network restrictions | | Chrome / Chromium | Requires one-time approval | See below | | Brave | Requires Shield disabled | See below | | Vivaldi | Requires one-time approval | Same as Chrome |
Chrome / Vivaldi: Local Network Access
Chrome may show a permission popup: "Allow [localhost:9001] to access your local network?"
- Click Allow when the popup appears
- The plugin will connect automatically
If no popup appears and the plugin stays disconnected, check chrome://flags/#private-network-access-respect-preflight-results -- disable it for local development.
Brave: Shield
- Click the Shield icon (lion) in the address bar
- Disable the Shield for
localhost:9001(or set to "No Blocking") - Reload the
Truncated for display — read the full file on GitHub.
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