Pixl
Turns AI coding hosts into a guided mobile-UI design tool with design interviews, token contracts, linters, and local browser preview.
README
Pixl
Open-source MCP server for designing mobile UIs. Pixl plugs into whatever AI coding host you already use (Claude Code, Cursor, …) and turns it into a guided mobile-UI design tool. Your host's model does the generating — Pixl supplies the taste it lacks: a locked design-system token contract, a linter that rejects off-standard output, and a local browser preview with a phone-frame gallery and a draggable user-journey flow map. Everything runs locally.
Status: v0.1, feature-complete — MCP server, workspace, live preview, design-system presets + token contract, screen generation with the taste linter, and the draggable user-journey flow canvas.
How it fits together
host (Claude Code / Cursor) ──MCP stdio──▶ pixl-mcp (Node/TS)
│ owns .pixl/ workspace, runs linter
▼
localhost:4321 Vite + React preview
├── Screen gallery (phone frames, live-reload)
└── Flow canvas (dotted bg, draggable)
State lives in a .pixl/ folder in your project: tokens.json, design/*.md, screens/*.html, flow.json.
Install
Pixl auto-starts when your host connects: it creates the .pixl/ workspace, boots the preview, and opens localhost:4321 in your browser. No pixl_init call needed — just point your host at it and start asking for screens.
npx (recommended):
Cursor — ~/.cursor/mcp.json:
{ "mcpServers": { "pixl": { "command": "npx", "args": ["-y", "pixl-mcp"] } } }
Claude Code:
claude mcp add pixl -- npx -y pixl-mcp
Docker (no Node needed; fully isolated). -p 4321:4321 forwards the preview; the sh -c wrapper reaps any prior container so relaunches don't clash on the port:
{
"mcpServers": {
"pixl": {
"command": "sh",
"args": [
"-c",
"docker rm -f pixl-mcp >/dev/null 2>&1; exec docker run --rm -i --name pixl-mcp -p 4321:4321 -v \"$PWD\":/work -w /work pixl-mcp"
]
}
}
}
Build the image first with docker build -t pixl-mcp . (or pull it once published).
Develop
npm install --include=dev # this machine has npm omit=dev set globally
npm run build # compile the server to dist/
npm run typecheck
npx vitest run # linter unit tests (pass/fail fixtures)
node scripts/smoke.mjs # workspace + preview API end-to-end
node scripts/mcp-smoke.mjs # drives the server as a real MCP client
node scripts/phase2-smoke.mjs # design system + screen plan
node scripts/phase3-smoke.mjs # write/lint screen: reject bad, accept fixed
node scripts/phase4-smoke.mjs # flow graph + drag-persist round-trip
Register a local build (from source)
Claude Code:
npm install --include=dev && npm run build
claude mcp add pixl -- node /absolute/path/to/pixl-mcp/dist/index.js
The preview auto-starts and opens localhost:4321 — then ask your assistant to set a design system and generate screens.
Tools
| Tool | Purpose |
|---|---|
pixl_init |
Re-open the preview / fetch its URL (auto-runs on startup — you don't call it) |
pixl_status |
Report workspace state |
pixl_list_presets / pixl_set_design_system / pixl_plan_screens |
Design system + screen plan |
pixl_write_screen / pixl_lint_screen |
Generate + lint screens |
pixl_set_flow |
User-journey flow graph |
MIT.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.