Medium Risk

patch_dashboard

Apply targeted changes to a dashboard

Risk signalsModifies dashboard panels and queries

Part of the Grafana server.

patch_dashboard can modify Grafana data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use patch_dashboard to create or modify resources in Grafana. 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 patch_dashboard 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 Grafana.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "patch_dashboard": {
      "limits": [
        {
          "counter": "patch_dashboard_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Grafana policy for all 29 tools.

Get this rule live on your own Grafana server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access patch_dashboard gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so patch_dashboard only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the patch_dashboard tool do? +

Apply targeted changes to a dashboard. It is categorised as a Write tool in the Grafana MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on patch_dashboard? +

Register the Grafana MCP server in PolicyLayer and add a rule for patch_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 Grafana. Nothing to install.

What risk level is patch_dashboard? +

patch_dashboard is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit patch_dashboard? +

Yes. Add a rate_limit block to the patch_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 patch_dashboard completely? +

Set action: deny in the PolicyLayer policy for patch_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 patch_dashboard? +

patch_dashboard is provided by the Grafana MCP server (grafana/mcp-grafana). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Grafana tool call.

Deterministic rules across all 29 Grafana 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.

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