roboflow-cloud-storage
Use when connecting cloud storage (AWS S3 / S3-compatible or Google Cloud Storage) to Roboflow to mirror images into a workspace — creating storage credentials, defining datasources (bucket-mirror configs), selecting objects with glob rules, validating access, and running/scheduling mirror jobs.
How do I install this agent skill?
npx skills add https://github.com/roboflow/computer-vision-skills --skill roboflow-cloud-storageIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill facilitates connecting cloud storage to Roboflow for image synchronization. It uses secure, out-of-band secret handling to prevent credentials from entering the AI context.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
For agents — source-of-truth: This skill is authored in
roboflow/computer-vision-skillsand shipped with the Roboflow plugin. If your client has loaded the plugin (you'll seeroboflow:<name>skills in your available skills list), use those local skills — they're read fresh from disk every session. The same content served as MCP resources atroboflow://skills/<name>/...is a fallback for clients without the plugin and may lag this repo. Don't callReadMcpResourceToolforroboflow://skills/...URIs when a localroboflow:<name>skill is available.
Cloud Storage (Datasources & Credentials)
Mirror a cloud bucket's contents into a Roboflow workspace so new objects flow in automatically. Two pieces work together:
- Credential — the secret Roboflow uses to reach the bucket (stored, masked server-side, reusable across datasources).
- Datasource — a bucket-mirror configuration: which bucket (via a credential), which objects (glob rules), and how they sync. "Datasource" is the user-facing name; the platform stores it as a bucket-mirror config.
Imports land at the workspace level. The datasource API cannot target a specific project/dataset today.
Only want to run a model/Workflow over the files and collect the outputs, without importing anything into Roboflow? That is batch processing — see the
roboflow-batch-processingskill. Mirroring composes with it too: imported files become Asset Library images, and bulk predictions over them run as Asset Library batch processing jobs (same skill).
Fast path — one call
connect_cloud_storage does the whole flow in one shot: (optionally) create a
credential, create the datasource, validate access, and start the first mirror
run. Prefer it for new setups.
- Reuse a credential: pass
credential_id(fromcredentials_list). - Create a new credential: pass
credential_name+credential_type(the secret is collected securely out-of-band — see Security). - Describe the datasource so it can be created first:
bucket_type(s3/gcs),bucket_name,region, plus optionalmirror_configsglob rules (see Datasources). The datasource must exist before anything can be validated or triggered — there is nothing to mirror without it. trigger(default true) starts a mirror run only if validation passes; triggering consumes credits.- Returns
{credentialId, credentialCreated, datasourceId, validation, triggered, batchIds?}. If a new credential was created but a later step failed, you getstatus: "partial"with the ids so you can clean up withcredentials_delete/datasource_delete.
Credentials
Security — secrets never enter the chat
The secret (keys, service-account JSON, password) is collected out-of-band
via MCP elicitation, never as a tool argument and never in the transcript or
model context. credentials_list returns only masked, non-secret fields.
If your client can't elicit securely, the tool returns
manual_entry_required with a URL to create the credential in the app
(app.roboflow.com/<workspace>/settings/datasources), then call
credentials_list to get its id.
Credential types
credential_type | Provider | Secret fields collected |
|---|---|---|
IAM | AWS S3 | accessKeyId, secretAccessKey, sessionToken? |
AssumeRole | AWS S3 | roleArn, externalId, sessionName? |
AssumeRoleWithWebIdentity | AWS S3 | roleArn, webIdentityAudience, webIdentityRoleArn, externalId, sessionName? |
gcs | Google Cloud Storage | projectId, credentialFile (full service-account JSON) |
usernamePassword | S3-compatible | username, password |
apiKey | S3-compatible | apiKey |
AWS PrivateLink (
require_vpce) requires anAssumeRoleWithWebIdentitycredential; the server rejects the datasource otherwise.
Datasources
Bucket
bucket_type:s3orgcsbucket_name(no scheme/path),region(e.g.us-east-1)endpoint: custom URL for S3-compatible providers (S3 only)
Mirror rules (mirror_configs)
Optional list; omit to mirror the whole bucket with default settings. Each rule selects a subset and controls sync behavior:
glob_patterns(list) — the key field. Selects objects, e.g.["images/**/*.jpg", "batch-*/**"]. Set it to avoid importing unwanted files or to split a bucket into multiple rules. Omit only when you truly want everything.glob_file_path— alternative: path to a manifest file in the bucket whose lines list object paths to import.id— rule id (auto-generated; pass an existing id on update to edit in place).settings(omitted keys use server defaults):removeOrphanedSourcesWhenDisappeared(default true) — delete mirrored images when the source object is removed.namingStrategy(fullPath|fileName|eTag|metadata, defaultfullPath);namingStrategyMetadataKeyrequired whenmetadata.updateImageWhenNewer(true) /updateImageStrategy(overwrite).updateMetadataWhenNewer(true) /updateMetadataStrategy(mergeBucketWinsdefault; alsooverwrite|merge|mergeUserWins|untilFirstChange|append).runScheduledEvery(hours, default 0 = off) — >0 enables a recurring mirror (fixed 24h cadence today; only on/off is honored).
Lifecycle & validation
- Create (
datasource_create, orconnect_cloud_storage). Nothing is mirrored yet. - Validate (
datasource_validate) — checkslistFiles,headFile,getFile, and per-ruleheadGlobFile; returns{checks, errors}. Run it to self-diagnose a bad credential/bucket before triggering. - Trigger (
datasource_trigger) — starts the mirror job; consumes compute/storage credits. Returns{batchIds}. - Poll (
datasource_job_getwith abatchId) —status(running/completed/failed), per-stagecounters,errors, timestamps.
Update (datasource_update): only fields you pass change; to change the
bucket pass bucket_type + bucket_name + region together.
Delete (datasource_delete): removes the config, not already-mirrored
images. Deleting a credential still referenced by a datasource makes its runs
fail.
MCP Tools Available
| Tool | Purpose |
|---|---|
connect_cloud_storage | End-to-end: credential + datasource + validate + first run |
credentials_list | List masked cloud-storage credentials |
get_aws_storage_credential_setup_link | Get a Roboflow app link for AWS storage credential setup; enter secrets in the app |
credentials_delete | Delete a credential |
datasources_list / datasource_get | List / inspect datasource configs |
datasource_create / datasource_update / datasource_delete | Manage a datasource |
datasource_validate | Check bucket access before a run |
datasource_trigger | Start a mirror run (consumes credits) |
datasource_job_get | Poll a mirror run's status and counters |
Related Pages
roboflow://skills/roboflow-data-management/SKILL— what to do with the images once mirrored (tags, splits, versions, search)roboflow://skills/roboflow-product-navigation/SKILL— the app'ssettings/datasourcespage
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/roboflow/computer-vision-skills/roboflow-cloud-storage">View roboflow-cloud-storage on skillZs</a>