Get a Kubernetes resource in the current cluster by providing its apiVersion, kind, optionally the namespace, and its name
Part of the Kubernetes server.
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AI agents call resources_get to retrieve information from Kubernetes without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though resources_get only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"resources_get": {}
}
}See the full Kubernetes policy for all 45 tools.
These attack patterns abuse exactly the kind of access resources_get gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Get a Kubernetes resource in the current cluster by providing its apiVersion, kind, optionally the namespace, and its name. It is categorised as a Read tool in the Kubernetes MCP Server, which means it retrieves data without modifying state.
Register the Kubernetes MCP server in PolicyLayer and add a rule for resources_get: 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 Kubernetes. Nothing to install.
resources_get 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 resources_get 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 resources_get. 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.
resources_get is provided by the Kubernetes MCP server (kubernetes-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 45 Kubernetes tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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