
Cosmic Intelligence
March 23, 2025

How to Build a Pinterest Clone with Svelte and Cosmic
In this tutorial, we'll build a Pinterest-style image discovery platform using Svelte for the frontend and Cosmic as our headless CMS backend. Our clone will feature a masonry grid layout, user collections, image uploads, and search functionality.
Tip: click the copy markdown button at the top of this page to copy the code to your clipboard and paste into your AI-powered code editor.
Project Setup
First, let's create a new Svelte project:
Setting Up Cosmic Backend
Create a new Cosmic bucket and use this improved seed script (saved as ) to set up your content structure:
Run the seed script with:
The script includes robust error handling to:
- Check if object types already exist before creating them
- Check if content already exists before creating duplicates
- Handle Cosmic API responses correctly
- Format metafields according to the Cosmic API requirements
Environment Setup
Create a file in your project root with your Cosmic credentials:
Building the Masonry Grid
Create a component for the masonry layout:
Creating the Pin Card Component
Create a component:
Implementing Search Functionality
Create a component:
Creating a Pin Detail Page
Create a file:
Creating a Board Detail Page
Create a component:
Creating a Main Page
Create a file that uses our components:
Creating a Layout
Create a file for consistent styling:
Running the Application
After setting up all components and seeding your Cosmic bucket, you can run the application:
Conclusion
This tutorial provides a complete foundation for a Pinterest clone using Svelte and Cosmic. The application features:
- A masonry grid layout for visually appealing pin display
- Individual pin detail pages
- Board collections to organize pins
- Search functionality by title, description, or tags
- Responsive design for all device sizes
One of the key aspects of this implementation is the robust error handling in the seed script, which ensures your Cosmic bucket is set up correctly even if you run the script multiple times.
For tags, we're using a comma-separated string approach, which is then parsed into an array in the components. This simplifies the data structure while still providing good UX.
To enhance your app further, consider adding:
- User authentication
- Pin saving functionality
- Pin upload capability with Cosmic Intelligence for auto-generating descriptions
- Infinite scrolling for the masonry grid
- Related pins recommendations
The full source code for this project provides a solid starting point for building your own image discovery platform with an efficient headless CMS backend.