List RBAC Roles with their permission rules.
AI agents call k8s_get_roles to retrieve information from Multi Cluster Kubernetes MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and displays existing RBAC role configurations without altering them. It is a read-only operation that queries cluster state for informational purposes. While knowledge of roles could inform privilege escalation attempts, the tool itself performs no destructive, write, or execute operations. Classification as Read is appropriate.
From the tool's definition Tool name is 'k8s_get_roles' and description states 'List RBAC Roles with their permission rules.' The verb 'List' indicates data retrieval with no modifications or side effects.
Documented attack patterns abuse exactly the kind of access k8s_get_roles gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Multi Cluster Kubernetes MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for k8s_get_roles:
{
"version": "1",
"default": "deny",
"tools": {
"k8s_get_roles": {}
}
} k8s_get_roles is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List RBAC Roles with their permission rules. It is categorised as a Read tool in the Multi Cluster Kubernetes MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Multi Cluster Kubernetes MCP Server MCP server in PolicyLayer and add a rule for k8s_get_roles: 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 Multi Cluster Kubernetes MCP Server. Nothing to install.
k8s_get_roles 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 k8s_get_roles 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 k8s_get_roles. 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.
k8s_get_roles is provided by the Multi Cluster Kubernetes MCP Server MCP server (razvanmacovei/k8s-multicluster-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Multi Cluster Kubernetes MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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57 Multi Cluster Kubernetes MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.