list_dashboards
Use this as the primary tool to retrieve a list of existing custom monitoring dashboards in a Google Cloud project. Custom monitoring dashboards let users view and analyze data from different sources in the same context. This is useful for understanding what custom dashboards are currently config...
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What list_dashboards does on Mcp
AI agents call list_dashboards 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 |
|---|---|---|---|
parent | string | Yes | Required. The scope of the dashboards to list. The format is: projects/[PROJECT_ID_OR_NUMBER] |
pageSize | integer | — | A positive number that is the maximum number of results to return. If unspecified, a default of 1000 is used. |
pageToken | string | — | Optional. If this field is not empty then it must contain the `nextPageToken` value returned by a previous call to this method. Using this field causes the meth |
Parameters from the server's own tool schema.
Why list_dashboards is rated Low
This tool only reads and lists existing dashboard configurations without any side effects. It queries data about available dashboards in a Google Cloud project, which is a classic Read operation. The blast radius of misuse is minimal, as an attacker would only gain visibility into dashboard configurations, not ability to modify infrastructure, execute operations, or access sensitive data within those dashboards.
From the tool's definition Tool description states it is used to "retrieve a list of existing custom monitoring dashboards". The action is purely informational—listing dashboards with no modification, deletion, or execution capability.
Attacks that exploit this kind of access
The rule that runs list_dashboards 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 list_dashboards, this is the rule to start with:
list_dashboards 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 list_dashboards call is checked against it from then on.
Questions about list_dashboards
Use this as the primary tool to retrieve a list of existing custom monitoring dashboards in a Google Cloud project. Custom monitoring dashboards let users view and analyze data from different sources in the same context. This is useful for understanding what custom dashboards are currently configured and available in a given project. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
list_dashboards accepts 3 parameters: parent, pageSize, pageToken. Required: parent. 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 list_dashboards: 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.
list_dashboards 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 list_dashboards 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 list_dashboards. 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.
list_dashboards is provided by the MCP server (https://monitoring.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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