get_dashboard

SERVERMcp SOURCEhttps://monitoring.googleapis.com/mcp

Low RISK CLASS

Category Read

Parameters 11 required

Recommended Allowedsee the rule below

Registry record Grade C, identity unverified Pull the record →

This record as markdown: /tools/com-googleapis-monitoring-mcp/get-dashboard.md

WHAT IT DOES

What get_dashboard does on Mcp

AI agents call get_dashboard 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
`name`	string	Yes	Required. The resource name of the Dashboard. The format is one of: - `dashboards/[DASHBOARD_ID]` (for system dashboards) - `projects/[PROJECT_ID_OR_NUMBER]/das

Parameters from the server's own tool schema.

RISK

Why get_dashboard is rated Low

This tool retrieves and displays monitoring dashboard data from Google Cloud without creating, modifying, deleting, or executing operations. It is a straightforward read operation with minimal blast radius if misused—an agent could only access existing dashboards it has permissions for, causing no data changes or resource impact.

From the tool's definition Tool description states it 'retrieve[s] a single specific custom monitoring dashboard' and 'let users view and analyze data'. The verb 'retrieve' and context of 'view' indicate data querying with no side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_dashboard 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 get_dashboard, this is the rule to start with:

get_dashboard Allowed

get_dashboard is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_dashboard": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp, apply this rule, and every get_dashboard call is checked against it from then on.

FAQ

Questions about get_dashboard

What does the get_dashboard tool do? +

Use this as the primary tool to retrieve a single specific custom monitoring dashboard from a Google Cloud project using the resource name of the requested dashboard. Custom monitoring dashboards let users view and analyze data from different sources in the same context. This is often used as a follow on to list_dashboards to get full details on a specific dashboard. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.

What parameters does get_dashboard accept? +

get_dashboard accepts 1 parameter: name. Required: name. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on get_dashboard? +

Register the MCP server in PolicyLayer and add a rule for get_dashboard: 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.

What risk level is get_dashboard? +

get_dashboard is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_dashboard? +

Yes. Add a rate_limit block to the get_dashboard 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.

How do I block get_dashboard completely? +

Set action: deny in the PolicyLayer policy for get_dashboard. 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.

What MCP server provides get_dashboard? +

get_dashboard 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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