get_k8s_rollout_status
Checks the current rollout status of a Kubernetes resource. This is similar to running kubectl rollout status.
This record as markdown: /tools/com-googleapis-container-mcp/get-k8s-rollout-status.md
What get_k8s_rollout_status does on Mcp
AI agents call get_k8s_rollout_status to retrieve information from Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | Required. The name of the resource to check. |
parent | string | Yes | Required. The cluster to check rollout status in. Format: projects/{project}/locations/{location}/clusters/{cluster} |
namespace | string | — | Optional. The namespace of the resource. If not specified, "default" is used for namespace-scoped resources. |
resourceType | string | Yes | Required. The type of resource to check. e.g. "deployment", "daemonset", "statefulset". |
Parameters from the server's own tool schema.
Why get_k8s_rollout_status is rated Low
This tool retrieves and reports the current rollout status of a Kubernetes resource without modifying, deleting, or executing any operations. It is a pure read operation that queries existing resource state, similar to inspection commands. No data is created, modified, or deleted, and no external operations are triggered.
From the tool's definition Tool description states 'Checks the current rollout status' which is a query operation equivalent to `kubectl rollout status`. The verb 'checks' and 'status' indicate read-only retrieval of state information with no side effects.
Attacks that exploit this kind of access
The rule that runs get_k8s_rollout_status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_k8s_rollout_status, this is the rule to start with:
get_k8s_rollout_status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp, apply this rule, and every get_k8s_rollout_status call is checked against it from then on.
Questions about get_k8s_rollout_status
Checks the current rollout status of a Kubernetes resource. This is similar to running kubectl rollout status. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
get_k8s_rollout_status accepts 4 parameters: name, parent, namespace, resourceType. Required: name, parent, resourceType. The full parameter table on this page comes from the server's own tool schema.
Register the MCP server in PolicyLayer and add a rule for get_k8s_rollout_status: 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 Mcp. Nothing to install.
get_k8s_rollout_status is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_k8s_rollout_status 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 get_k8s_rollout_status. 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.
get_k8s_rollout_status is provided by the MCP server (https://container.googleapis.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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