databricks_run_quality_monitor_refresh

What databricks_run_quality_monitor_refresh does on Databricks MCP Server

AI agents invoke databricks_run_quality_monitor_refresh to trigger actions in Databricks MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

Why databricks_run_quality_monitor_refresh is rated High

This tool executes a refresh operation on a quality monitor, which is an external system action whose side effects depend on the monitor configuration and data state. While not immediately destructive, it triggers code/process execution in Databricks infrastructure. Execute is the appropriate category as it runs an operation whose effects are operational and non-reversible in nature (monitoring state changes).

From the tool's definition Tool name 'databricks_run_quality_monitor_refresh' indicates it triggers execution of a quality monitor refresh operation. The verb 'run' combined with the imperative action 'refresh' suggests initiating an external operation.

The rule that runs databricks_run_quality_monitor_refresh safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Databricks MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For databricks_run_quality_monitor_refresh, this is the rule to start with:

{
  "version": "1",
  "default": "deny",
  "tools": {
    "databricks_run_quality_monitor_refresh": {
      "limits": [
        {
          "counter": "databricks_run_quality_monitor_refresh_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

Questions about databricks_run_quality_monitor_refresh