This record as markdown: /tools/com-googleapis-container-mcp/update-cluster.md
What update_cluster does on Mcp
AI agents use update_cluster to create or update resources in Mcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | Required. The name (project, location, cluster) of the cluster to update. Specified in the format `projects/*/locations/*/clusters/*`. |
update | string | Yes | Required. A description of the update represented as a string using JSON format. The full update request object can be found at https://cloud.google.com/contain |
Parameters from the server's own tool schema.
Why update_cluster is rated Medium
This tool modifies cluster state (likely configuration, scaling, or settings) but does not irreversibly delete resources, nor does it execute arbitrary code or move funds. However, misuse could impact cluster availability or security posture, warranting 'high' severity due to the blast radius of cluster-level modifications in a Kubernetes environment.
From the tool's definition Tool name 'update_cluster' and description 'Updates a specific GKE cluster' indicate modification of existing cluster configuration. Update operations are Write-category actions.
Attacks that exploit this kind of access
The rule that runs update_cluster 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 update_cluster, this is the rule to start with:
update_cluster stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. 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 update_cluster call is checked against it from then on.
Questions about update_cluster
Updates a specific GKE cluster. It is categorised as a Write tool in the Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_cluster accepts 2 parameters: name, update. Required: name, update. 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 update_cluster: 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.
update_cluster 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 update_cluster 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 update_cluster. 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.
update_cluster 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.
More on , and thousands of servers like it.
This server
Across the catalogue