Install (deploy) a Helm chart to create a release in the current or provided namespace
Part of the Kubernetes server.
Free to start. No card required.
AI agents use helm_install to create or modify resources in Kubernetes. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call helm_install repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Kubernetes.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"helm_install": {
"limits": [
{
"counter": "helm_install_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Kubernetes policy for all 45 tools.
These attack patterns abuse exactly the kind of access helm_install gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Install (deploy) a Helm chart to create a release in the current or provided namespace. It is categorised as a Write tool in the Kubernetes MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kubernetes MCP server in PolicyLayer and add a rule for helm_install: 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.
helm_install 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 helm_install 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 helm_install. 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.
helm_install 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.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.