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Amazon S3 is a cloud object storage service. It lets your Lovable app read data files such as CSV, JSON, Parquet, and more directly from your S3 buckets, so you can build apps that work with external datasets, batch exports, and file-based data sources. With AWS S3, your app can:
  • Read CSV, JSON, and other data files from S3 buckets
  • List and browse objects in a bucket with prefix filtering
  • Integrate external data sources into your Lovable app
  • Access batch data exports from enterprise data pipelines
AWS S3 is a good fit when your app needs to pull data from files stored in S3, such as analytics exports, data pipeline outputs, or shared datasets.

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Common use cases and example apps

Example appExample promptDescription
Data explorerBuild a data explorer that lists files in my S3 bucket and lets me preview CSV and JSON files.Browse and preview files stored in S3 without leaving your app.
The app lists objects in the bucket and renders previews of supported file formats inline.
Analytics dashboardBuild a dashboard that reads a daily export CSV from S3 and shows charts for revenue and user signups.Turn S3 data exports into live dashboards.
The app reads the latest export file from your bucket and visualizes key metrics automatically.
Report viewerBuild an internal report viewer that loads JSON reports from S3 and displays them in a searchable table.Give your team a clean interface to browse reports.
The app pulls JSON files from a specific S3 prefix and renders them as filterable, sortable tables.
File download portalBuild a file download portal where users can browse and download files from our shared S3 bucket.Create a simple self-service file access layer on top of S3.
The app lists available files and lets users download them directly, without needing AWS console access.
Data pipeline monitorBuild a tool that checks my S3 bucket for new data files and shows when each pipeline last wrote output.Monitor data pipeline health by tracking file freshness.
The app lists objects by prefix and surfaces the last-modified timestamps so you can spot stale or missing exports.

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How AWS S3 connections work

Each AWS S3 connection is tied to a single S3 bucket. When you connect AWS S3, you provide IAM credentials with read access to that bucket. Within your Lovable workspace:
  • You can create multiple AWS S3 connections.
  • Each connection targets a specific bucket and AWS region.
  • Each connection uses its own IAM credentials.
  • Multiple projects within a single workspace can use the same connection.
This makes it easy to connect different buckets (for example, production data and staging data) or separate access by team. AWS S3 uses Lovable’s gateway architecture for secure credential handling and automatic request signing. See Gateway-based connectors for details on authentication and usage limits.
The AWS S3 connector provides read-only access. Your app can list and download objects but cannot upload, modify, or delete files in the bucket.

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How to connect AWS S3

Workspace admins and owners can connect AWS S3. When a connection is created, the S3 bucket becomes available across all projects in the workspace.

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Prerequisites

Before connecting AWS S3, make sure you have:
  • An AWS account with access to the S3 bucket you want to connect
  • An IAM user with read-only access to the bucket (see below)
  • The bucket name and AWS region
  • Lovable workspace admin or owner role

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Step 1: Create an IAM user with read-only access

Before setting up the connection in Lovable, create an IAM user in AWS with the minimum permissions needed.
1

Open the AWS IAM console

Go to the AWS IAM console and create a new IAM user, or use an existing one, for Lovable to use.
2

Attach a read-only S3 policy

Create and attach an inline policy, or managed policy, with the following permissions. Replace YOUR-BUCKET-NAME with your actual bucket name:
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "ListBucket",
      "Effect": "Allow",
      "Action": ["s3:ListBucket", "s3:GetBucketLocation"],
      "Resource": "arn:aws:s3:::YOUR-BUCKET-NAME"
    },
    {
      "Sid": "ReadObjects",
      "Effect": "Allow",
      "Action": ["s3:GetObject"],
      "Resource": "arn:aws:s3:::YOUR-BUCKET-NAME/*"
    }
  ]
}
Keep the policy scoped to only the bucket you want to connect. Avoid using wildcard (*) resources.
3

Generate access keys

In the IAM user’s Security credentials tab, create an access key. Save both the Access Key ID and Secret Access Key, since you’ll need them in the next step.
The secret access key is shown only once. Store it securely. If you lose it, you’ll need to create a new access key pair.

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Step 2: Connect AWS S3 to Lovable

When you connect AWS S3, the bucket’s contents will be accessible to all users in your workspace.
1

Navigate to the AWS S3 connector

Go to Settings → Connectors → Shared connectors and select AWS S3.
2

Add a new connection

Click Add connection.
3

Name the connection

In Display name, enter a name for the connection, for example S3 (Production Data).
4

Configure the connection

Fill in the required fields:
  • Bucket name: the name of the S3 bucket (for example, my-data-bucket)
  • AWS region: the region where the bucket is located (for example, us-east-1)
  • Access key ID: the IAM access key ID from the previous step
  • Secret access key: the IAM secret access key from the previous step
5

Connect

Click Connect. Lovable verifies the credentials by checking access to the bucket. If verification succeeds, the connection is ready to use.
When connected, your Lovable apps can start reading data from the S3 bucket.

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Limitations

The AWS S3 connector does not support:
  • Writing, uploading, or deleting objects in the bucket (it has read-only access)
  • Connecting to S3-compatible services other than AWS S3, such as MinIO or DigitalOcean Spaces
  • Per-user AWS login where each end user connects their own AWS account
  • Real-time event notifications or S3 event triggers
Editors and above can remove specific projects from a connection without deleting the connection entirely. The connection will remain available for other projects. To unlink projects:
1

Navigate to connectors

Go to Settings → Connectors → Shared connectors and select .
2

Open the connection

Open the connection you want to manage.
3

Select projects

Under Linked projects, check the projects you want to unlink.
4

Confirm

Click Unlink projects and confirm.
When unlinked, those projects will no longer have access to through this connection. If a project needs again, you can link it to any available connection.

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How to delete a connection

Workspace admins and owners can delete connections.
Deleting a connection is permanent and cannot be undone. It will remove the credentials from all linked projects, and any apps using this connection will stop working until a new connection is added.
Before deleting, review the Linked projects section to see which projects are currently using the connection. To delete a connection:
1

Navigate to connectors

Go to Settings → Connectors → Shared connectors and select .
2

Open the connection

Open the connection you want to remove.
3

Review linked projects

Review the Linked projects section.
4

Delete

Under Delete this connection, click Delete and confirm.