> ## Documentation Index
> Fetch the complete documentation index at: https://claude.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Cloud storage

> Connect Amazon S3, Google Cloud Storage, or Azure Blob Storage so Claude can read data and write results in place, with your permission.

Connect Amazon S3, Google Cloud Storage, or Azure Blob Storage so Claude can read data and write results in place, with your permission.

In **Settings > Credentials**, choose **AWS**, **Google Cloud**, or **Microsoft Azure**, then Connect. Provide the credential (access key, service-account JSON, HMAC key, service principal, or connection string) and list the bucket names (AWS, GCP) or **Blob containers** (Azure) this credential covers. S3-compatible stores use the AWS form with the **S3-compatible endpoint** field; you'll need to allowlist that endpoint host separately.

Listing a bucket adds its address to the sandbox network allowlist so code can reach it without a per-call card. Access within the bucket is still limited to the credential's permissions. Credentials are encrypted on your computer and sent only to the provider they belong to.

Claude reads and writes objects with ordinary code using the provider's Python library (`boto3`, Azure SDK). **Settings > Storage** lists connected credentials and lets you browse and import objects (up to 100 GB) or export artifacts.

<Note>
  From code, reach Google Cloud Storage with an **HMAC key** via `boto3`, or use the import/export flow. `gsutil`, `gcloud storage`, and the google-cloud-storage Python library use path-style addresses that aren't reachable from the sandbox.
</Note>

<Warning>
  Any code Claude writes can use credentials you add here. If a bucket should never be reachable from an analysis session, don't add its credential.
</Warning>