AI agents use create_bucket to create or update resources in Storage — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Storage environment.
This tool creates a new storage resource (bucket) which is a reversible operation—buckets can be deleted. It modifies the cloud infrastructure state by adding a new resource, but does not delete, execute arbitrary code, or move money.
From the tool's definition Tool name 'create_bucket' and description 'Creates a new bucket with specified configuration' indicate data structure creation. In GCS context, a bucket is a top-level storage container.
Attacks that exploit this kind of access
Creates a new bucket with specified configuration. It is categorised as a Write tool in the Storage MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Storage MCP server in PolicyLayer and add a rule for create_bucket: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Storage. Nothing to install.
create_bucket is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_bucket rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for create_bucket. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
create_bucket is provided by the Storage MCP server (@google-cloud/storage-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.