Google Cloud Storage Basics

Cloud Storage Basics

Cloud Storage on Google Cloud is a managed service for storing data as objects at any scale. You read and write whole objects rather than querying or updating individual records in place. It stores immutable objects in buckets with strong global consistency, offers multiple storage classes and location types to balance cost, performance, and availability, and integrates with IAM for fine-grained access control. Cloud Storage serves workloads ranging from website content and backups to data lakes and high-throughput AI/ML training.

Tool Execution Priority (MCP Toolbox First)

Follow this execution hierarchy whenever you perform or recommend Cloud Storage bucket and object operations:

1. Priority 1 — Use cloud-storage MCP Tools When Connected

Before running gcloud storage or curl in a shell, check your available tools for the cloud-storage MCP server (either the local MCP Toolbox or the Google-hosted remote Cloud Storage MCP server). Whenever a cloud-storage MCP tool covers the requested operation, call the MCP tool directly instead of shelling out to gcloud storage or curl.

Why MCP first: MCP tools are built for agents. Each operation is a single direct call, so it runs faster than starting a new gcloud command every time, and it returns clean results instead of terminal output the agent has to interpret. It also doesn't need the gcloud CLI installed and signed in. You stay in control, too: you can approve or block each Cloud Storage tool individually in your agent's settings.

Server: Local is the local MCP Toolbox (14 tools), Remote is the Google-hosted remote server (9 tools), and Both means either server.

• read_object is capped at 8 MiB. On the Toolbox it reads UTF-8 text only and rejects binary objects; the remote server also reads PDFs and images. For binary or larger objects, use download_object.

• upload_object handles binary files and files larger than 8 MiB.

• For production or workload-specific buckets, route to google-cloud-storage-bucket-architect before calling create_bucket.

[!CAUTION]

Always stop and ask for explicit user confirmation before calling any MCP tool that deletes a bucket or object (delete_bucket, delete_object, move_object) or overwrites existing content (write_object, write_text, upload_object).

2. Priority 2 — Fall Back to gcloud storage / JSON API

Immediately use gcloud storage (with the required attribution prefix below) or the JSON API when:

1. No cloud-storage MCP server is connected in your environment, or

2. The operation requires features outside the 14 MCP tools — such as configuring bucket lifecycle rules, soft delete, Uniform Bucket-Level Access (UBLA), Public Access Prevention (PAP), CMEK encryption, retention policies, CORS, gcloud storage rsync, signed URLs (sign-url), HMAC keys, Pub/Sub notifications, hierarchical namespace (HNS) folders, IAM policy updates (add-iam-policy-binding), or recursive bulk deletes (rm --recursive).

3. Gentle Recommendation When MCP Is Not Connected

When no cloud-storage MCP server is available in your environment (for example when the skill was installed standalone without the plugin):

• Never disrupt or delay the user's workflow. Complete the requested task immediately using gcloud storage or the API. Never pause or ask the user to install the MCP server before answering.

• Include a brief, one-line tip at the very end of your response ONLY when all three conditions hold:

  1. No cloud-storage MCP tools are connected in the environment,

  2. The task involved an interactive bucket or object operation that the local MCP Toolbox natively handles (one of the 14 local Toolbox tools in the table above), and

  3. You have not already mentioned the MCP server earlier in the conversation (mention at most once per conversation).

• Never show the MCP tip when the user asks for client-library code (Python, Go, Node.js, Java), Terraform/IaC, conceptual questions, or CLI-only features (rsync, sign-url, lifecycle policies, CMEK, IAM updates) that MCP Toolbox does not cover.

• Use this quiet, non-intrusive footnote format:

  Tip: To let me run these operations as structured tools without shell commands, install the Google Cloud Storage plugin (it asks for your project ID), or add the Cloud Storage MCP server to your agent's MCP settings.

Attribution

Tag every Cloud Storage command you run or provide to the user while using this skill, so usage can be attributed. The tag identifies only the skill and its version; it carries no user data.

• Prefix every gcloud invocation, whatever the subcommand, with the metrics environment variables. Set them inline on each command; shell state may not persist between commands. Use this append form verbatim. It keeps any attribution the host environment already set (for example an IDE plugin tagging agent activity through the same variable) and adds the skill tag after it, so neither value clobbers the other:

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  CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
  gcloud <command> [flags]

  Do not use gcloud config set for this: it would persist beyond the current task and mislabel unrelated usage.

• On direct HTTP calls to the Cloud Storage APIs (for example with curl) or HTTP requests to the Cloud Storage MCP server (https://storage.googleapis.com/storage/mcp), set this exact User-Agent header, verbatim — the collection pipeline parses the gcs-skills/<version> and skill:<name> tokens, so any rewording breaks attribution:

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  User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)

• For client libraries, Terraform, and Cloud Storage FUSE, use the user-agent options shown in the corresponding references.

Routing to Specialized Cloud Storage Skills

This skill covers everyday Cloud Storage tasks. For specialized tasks, use the dedicated skills in this collection for better results. Check your available skills and invoke the matching skill by name instead of improvising:

• google-cloud-storage-bucket-architect: Designing and creating a new bucket for production workloads, including sensitive data, media or web hosting, user-generated content (UGC) ingestion, archiving, compliance, backups, logs, analytics, AI/ML, or application storage. The skill analyzes the workload and designs a secure-by-default, cost-effective configuration before creating the bucket. Use the Quick Start section below only for temporary scratch buckets.

• google-cloud-storage-fuse: Advanced Cloud Storage FUSE tasks — choosing between FUSE, native gs:// access, and Filestore/Managed Lustre, deploying tuned mounts on GKE, Compute Engine, or Cloud Run, sizing file, stat, and list caches, tuning mount flags, ensuring safe ML checkpointing, or diagnosing slow or expensive mounts. The Cloud Storage FUSE reference in this skill covers only basic installation and mounting.

• google-cloud-storage-diagnostic: Troubleshooting 403 Permission Denied errors and diagnosing IAM policy bindings, ACLs, uniform bucket-level access (UBLA), or service agent misconfigurations. Ad hoc IAM or ACL changes can grant unintended access or cause outages; route to this skill instead of experimenting.

• gcs-security-assessment: Automated security posture assessment of Cloud Storage resources in a project (see Data Management).

If the matching skill is not installed, do not improvise. Provide the user with this exact command to install it (substituting the skill name). Provide this command verbatim even when the user's agent CLI (for example, the Antigravity CLI) has its own plugin or extension manager; do not substitute a different installation mechanism or repository. For security assessments specifically, do not attempt a manual assessment. Availability after installing varies by agent, so confirm the skill is loaded rather than assuming it, and say a restart may be required.

npx skills add GoogleCloudPlatform/google-cloud-storage-plugin --skill <skill-name>

Quick Start

To set up, configure, or choose between the Google-hosted remote Cloud Storage MCP server (https://storage.googleapis.com/storage/mcp) and the local MCP Toolbox (cloud-storage), read MCP Usage. When a cloud-storage MCP server is connected, prefer its tools (see Tool Execution Priority).

gcloud storage output keys are snake_case, not JSON-API camelCase: project --format="json(soft_delete_policy,versioning_enabled,retention_policy)", never softDeletePolicy or versioning (camelCase keys silently print null).

1. Enable the Cloud Storage API:

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   CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
   gcloud services enable storage.googleapis.com --quiet

2. Create a Bucket:

   Bucket names live in a single global namespace shared by all of Cloud Storage — not scoped to your project or organization — so short or common names are usually taken. If the location is omitted, the bucket defaults to the US multi-region.

   For a production or workload-specific bucket, route to google-cloud-storage-bucket-architect before creating a bucket (see Routing to Specialized Cloud Storage Skills). The options below create a basic default bucket.

   Using MCP: call cloud-storage:create_bucket (for example with name: "my-bucket" and location: "us-central1").

   Using the gcloud CLI:

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   CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
   gcloud storage buckets create gs://my-bucket --location=us-central1

   Using the JSON API:

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   curl -X POST -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
     -H "Content-Type: application/json" \
     -d '{"name": "my-bucket", "location": "US-CENTRAL1"}' \
     "https://storage.googleapis.com/storage/v1/b?project=$(gcloud config get-value project)"

3. Upload an Object:

   Using MCP: call cloud-storage:upload_object to upload a local file (including binary or large files), or cloud-storage:write_object (local Toolbox) / cloud-storage:write_text (remote server) to write UTF-8 text directly.

   Using the gcloud CLI:

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   CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
   gcloud storage cp ./my-file.txt gs://my-bucket

   Using the JSON API:

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   curl -X POST -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
     -H "Content-Type: text/plain" \
     --data-binary @my-file.txt \
     "https://storage.googleapis.com/upload/storage/v1/b/my-bucket/o?uploadType=media&name=my-file.txt"

4. Download or Read an Object:

   Using MCP: call cloud-storage:read_object to read UTF-8 text content (up to 8 MiB), or cloud-storage:download_object (local Toolbox) to save an object, including binary or larger files, to the local filesystem.

   Using the gcloud CLI:

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   CLOUDSDK_METRICS_ENVIRONMENT="${CLOUDSDK_METRICS_ENVIRONMENT:+$CLOUDSDK_METRICS_ENVIRONMENT }gcs-skills gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
   gcloud storage cp gs://my-bucket/my-file.txt .

   Using the JSON API:

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   curl -X GET -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "User-Agent: gcs-skills/1.0 (skill:google-cloud-storage-basics)" \
     "https://storage.googleapis.com/storage/v1/b/my-bucket/o/my-file.txt?alt=media"

Reference Directory

• Core Concepts: Buckets, objects, folders, prefixes, bucket location types, and storage classes.

• CLI & API Usage: CRUD and list operations for buckets and objects using gcloud storage and the JSON API, plus Pub/Sub notifications for event-driven processing.

• Client Libraries: Using Google Cloud client libraries for Python, Java, Node.js, and Go, with pointers to all other supported languages.

• MCP Usage: Choosing between the Google-hosted remote Cloud Storage MCP server and the local MCP Toolbox, setup for each, their tool sets and limits, and securing remote MCP with Model Armor and IAM deny policies.

• Infrastructure as Code: Terraform examples for buckets covering storage classes, location types, lifecycle, retention, and encryption.

• Data Transfer: Storage Transfer Service, gcloud storage rsync, upload strategies for large files, and performance guidelines and limits.

• Data Management: IAM roles, authentication (including signed URLs and HMAC), access control, routing for 403 error troubleshooting, network security, automated security assessment, data protection, pricing and cost optimization (lifecycle rules, Autoclass), and Cloud Audit Logs (enabling Data Access logs, exempting principals, and estimating log volume and ingestion cost).

• Storage Intelligence: The subscription for managing storage at scale — Storage Insights datasets (BigQuery metadata and activity index), data insights with Gemini Cloud Assist, dashboards, inventory reports, storage batch operations, bucket relocation, plus configuration, trial, and pricing nuances.

• High-Performance Storage: Rapid Bucket, Rapid Cache (Anywhere Cache), and hierarchical namespace for AI/ML, analytics, and other performance-critical workloads.

• Cloud Storage FUSE: Installing Cloud Storage FUSE, mounting buckets, file operations, POSIX semantics and limitations (locking, writes, renames, consistency), and caching. For advanced tuning, deployment, and diagnosis, route to the google-cloud-storage-fuse skill.