With over 84,000 GitHub stars since its April 2026 launch, Open Design has emerged as the definitive open-source alternative to Anthropic's Claude Design. Rather than shipping its own language model, Open Design acts as an agent-agnostic design orchestration layer that auto-detects 25+ coding CLI executables on your PATH — including Claude Code, Codex, Cursor, Gemini CLI, OpenCode, Qwen, GitHub Copilot CLI, Hermes, and Kimi — or connects to any OpenAI-compatible endpoint via its built-in BYOK proxy at /api/proxy/stream. The platform introduces a file-based protocol where SKILL.md files define composable design workflows and DESIGN.md files establish version-controlled brand systems, currently shipping 31 first-party skills and 72 brand-grade design systems. Output spans web and mobile prototypes, live dashboards, presentation decks, raster images, video, and HyperFrames motion graphics, with export pipelines for HTML, PDF, PPTX, MP4, and ZIP. The daemon architecture uses SQLite for project state and serves a sandboxed iframe preview renderer with vendored React and Babel for JSX artifacts. Deployment options include the native desktop app for macOS, Windows, and Linux, local daemon mode via pnpm tools-dev, a single-container Docker Compose path serving both API and Next.js frontend on port 7456, and Vercel deployment for the web layer. On RepoCloud, deploy Open Design on a dedicated VPS with full root SSH access, persistent storage for your design systems and generated artifacts, and complete control over which AI providers and agent CLIs your instance connects to, all under the Apache-2.0 license.

Prompt, run, edit, and deploy full-stack Node.js applications from a browser tab: Bolt.diy is the official open-source version of Bolt.new's AI coding agent. Its foundation is StackBlitz's WebContainer technology - a sandboxed in-browser Node.js environment where the AI controls the whole stack: filesystem, npm, dev servers, terminal, and browser console. That means the agent does not just generate code; it installs dependencies, runs Vite or Next.js, reads errors, and fixes them. The defining difference from Bolt.new is model choice per prompt: 19+ providers including OpenAI, Anthropic, Gemini, DeepSeek, Groq, Mistral, Amazon Bedrock, and local models via Ollama or LMStudio, extensible through the Vercel AI SDK. Development ergonomics include live preview, a diff view of AI changes, codebase search, file locking to prevent generation conflicts, 15+ starter templates (React, Vue, Next.js, Astro, Svelte, Expo), and MCP support for external tools. Projects integrate with Git and Supabase, and deploy in one click to Vercel, Netlify, or GitHub Pages.

Open Lovable from the Firecrawl team delivers the first truly open-source alternative to Lovable.dev — a chat-driven AI copilot that takes any website URL and regenerates it as a complete, editable React application with TypeScript and Tailwind CSS in seconds. The pipeline combines Firecrawl's intelligent web scraping for JavaScript-rendered pages and single-page applications with your choice of AI provider — Claude, GPT-4, Google Gemini, or Groq — to analyze HTML structure, extract layouts and styling, decompose pages into proper React components, and generate production-ready code following modern best practices. Live preview runs in a secure sandbox environment using Vercel Sandbox with OIDC authentication or E2B Cloud, letting you see results immediately and iterate through natural language chat to request changes like Tailwind migration, componentization, SEO improvements, accessibility fixes, or custom form implementations. The optional Morph LLM fast-apply path accelerates small edits by applying diffs directly without full regeneration. The provider-agnostic architecture means you control costs by routing to different models — use Groq for fast iterations and Claude for complex layouts. Project structure follows Next.js conventions with organized app, components, atoms, styles, utils, and hooks directories. Deploy via pnpm with Node.js 18+ requiring only a Firecrawl API key, one AI provider key, and a sandbox provider configuration. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With 15,500 GitHub stars and over 1,100 forks, Plandex delivers a terminal-based AI coding agent purpose-built for the complex, multi-file tasks that overwhelm single-file AI assistants. The Go-powered server maintains a cumulative diff review sandbox that quarantines all AI-generated changes from your project files until you explicitly approve them — enabling 20-file refactors where you cherry-pick good changes and reject bad ones without touching git. A 2M token effective context window loads only what each step requires, while tree-sitter project maps index repositories exceeding 20M tokens across 30+ programming languages, providing structural awareness of class hierarchies, function signatures, and import graphs without burning tokens on full file content. The configurable model pack system assigns different models to different roles — Claude for planning, GPT for coding, Gemini for summarization — supporting Anthropic, OpenAI, Google, OpenRouter, Azure OpenAI, AWS Bedrock, DeepSeek, Perplexity, and Ollama for local models. Full auto mode handles end-to-end autonomous workflows including high-level planning, context loading, implementation, terminal command execution, and automated debugging of both terminal and browser applications. The interactive REPL provides fuzzy auto-complete, version-controlled sandbox branching, rewind to any previous point, and Git integration for commit message generation. The Plandex Server exposes 60+ REST API endpoints for programmatic orchestration across organizations, projects, plans, and branches. Deploy via Docker Compose for self-hosted operation with your own API keys. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Describe a component in natural language and watch it render: OpenUI, from Weights & Biases, is an open alternative to Vercel's v0. Type a prompt like "a dark-themed dashboard with a sidebar and charts" and the LLM renders working HTML with Tailwind styling live in the browser. You then iterate conversationally, asking for changes until the design is right, and convert the result to React, Svelte, or Web Components for use in a real project. The backend is Python with LiteLLM routing, so it works with OpenAI, Anthropic, Gemini, Groq, and Mistral API keys, or fully offline against local Ollama models, including vision models like LLaVA that can generate UI from screenshot input - feed a screenshot and the model reproduces or riffs on an existing interface. Generated markup is inspectable at any point, with light and dark mode toggles, theme selection, and responsive previews across device sizes. The practical effect is compressing the mockup-review-revise loop from hours to minutes: a described layout renders in seconds and iterates through follow-up prompts, and because output converts to real framework code, prototypes feed directly into production codebases instead of staying trapped in a design tool. Self-hosting keeps unreleased product interfaces and prompts on your own server, and LiteLLM routing lets you pick the model per task - a cheap fast model for rough drafts, a stronger one for final passes, or free local models for unlimited experimentation.

Sketch a wireframe, get working code: Draw a UI turns hand-drawn layouts into web interfaces. It pairs the open-source tldraw canvas with an OpenAI vision model: you sketch a layout - boxes, labels, buttons, arrows, whatever communicates the idea - select the drawing, and click Make Real. The app snapshots your selection as a PNG, sends it to the vision API with instructions to return a single HTML file styled with Tailwind CSS, and renders the result in an iframe directly on the canvas next to your sketch. The loop is iterative: annotate the generated prototype or redraw parts of it, select both the sketch and the previous result, and generate again - the model receives the earlier HTML as context and produces an updated version. Built by Figma engineer Sawyer Hood as one of the first viral GPT-4 Vision demos and the basis for tldraw's "Make Real", it is a Next.js app that runs against your own OpenAI API key. Self-hosting matters here: the upstream demo ships without authentication, so a private deployment keeps your API key from being drained by strangers. MIT-licensed.