get_k8s_resource
Gets one or more Kubernetes resources from a cluster. Resources can be filtered by type, name, namespace, and label selectors. Returns the resources in YAML format. This is similar to running kubectl get.
This record as markdown: /tools/com-googleapis-container-mcp/get-k8s-resource.md
What get_k8s_resource does on Mcp
AI agents call get_k8s_resource 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 | — | Optional. The name of the resource to retrieve. If not specified, all resources of the given type are returned. |
parent | string | Yes | Required. The cluster, which owns this collection of resources. Format: projects/{project}/locations/{location}/clusters/{cluster} |
namespace | string | — | Optional. The namespace of the resource. If not specified, all namespaces are searched. |
outputFormat | string | — | Optional. The output format. One of: (table, wide, yaml, json). If not specified, defaults to table. When both custom_columns and output_format are specified, o |
resourceType | string | Yes | Required. The type of resource to retrieve. Kubernetes resource/kind name in singular form, lower case. e.g. "pod", "deployment", "service". |
customColumns | string | — | Optional. Custom columns to display in table output. Accepts either kubectl custom-columns format (e.g., "NAME:.metadata.name,IMAGE:.spec.containers[*].image") |
fieldSelector | string | — | Optional. A field selector to filter resources. |
labelSelector | string | — | Optional. A label selector to filter resources. |
Parameters from the server's own tool schema.
Why get_k8s_resource is rated Low
Even though get_k8s_resource only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs get_k8s_resource 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_resource, this is the rule to start with:
get_k8s_resource 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_resource call is checked against it from then on.
Questions about get_k8s_resource
Gets one or more Kubernetes resources from a cluster. Resources can be filtered by type, name, namespace, and label selectors. Returns the resources in YAML format. This is similar to running kubectl get. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
get_k8s_resource accepts 8 parameters: name, parent, namespace, outputFormat, resourceType, customColumns, fieldSelector, labelSelector. Required: 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_resource: 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_resource 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_resource 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_resource. 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_resource 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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