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Premium Figma and Framer UI kit with hundreds of components, variants and icons for building polished, themeable sites.
Composio connects apps to LLMs and IDEs with 250+ MCP servers; high-traffic developer platform.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Vibe-coding builder creating full-stack apps by chatting with AI.
Pay-as-you-go API aggregating thousands of image, video, audio and LLM models with custom inference hardware for lower per-request cost.
No public pricing
Free trial available
- ✦300+ Figma UI components
- ✦2,000+ Figma variants
- ✦2,116 icons
- ✦Framer-ready components and templates
- ✦Deep theming (glass, line, flat styles)
- ✦Adaptive layouts with variables
- ✦Managed MCP Server
- ✦MCP Integrations
- ✦Managed Auth
- ✦Improved tool accuracy
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Single API for image, video, audio, 3D and LLM models
- ✦Standardized model addressing across hosted, partner and custom uploads
- ✦Support for LoRAs, ControlNets, VAEs and embeddings on open-source models
- ✦WebSocket and REST access with async webhook delivery
- ✦Pay-per-request billing with no infrastructure to manage
- ✦Raw serverless GPU/CPU compute for custom workloads
- →Build a website or app UI in Figma
- →Hand off Figma designs to Framer
- →Speed up prototyping with prebuilt components
- →Connect Agents, LLMs, and IDEs with 250+ fully managed MCP servers.
- →Connect Agents with 15k+ tools through Composio’s Model Context Protocol (MCP) servers
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
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- →Adding AI image or video generation to an app without managing infra
- →Batching multi-modal generation tasks in one API call
- →Running custom fine-tuned models via Model Upload
- →Cutting inference costs at high generation volume