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stop_watcher

Stop the notification watcher.

How to control stop_watcher ↓

What stop_watcher does on Openowl

AI agents invoke stop_watcher to trigger actions in Openowl. 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.

High Risk

Why stop_watcher needs a policy

Stopping a watcher constitutes executing an external operation that modifies system state by halting an ongoing service. While not destructive (reversible by restarting), it is an Execute action that triggers external effects on the target system. The blast radius is medium because disabling notification monitoring could disrupt expected system behavior or workflows dependent on that watcher.

From the tool's definition Tool name is 'stop_watcher' and description states 'Stop the notification watcher.' This terminates an active monitoring process on the desktop.

Documented attack patterns abuse exactly the kind of access stop_watcher gives an agent:

How to control stop_watcher

PolicyLayer is an MCP gateway — it sits between your AI agents and Openowl, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_watcher:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "stop_watcher": {
      "limits": [
        {
          "counter": "stop_watcher_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

stop_watcher stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Openowl — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about stop_watcher

What does the stop_watcher tool do? +

Stop the notification watcher. It is categorised as a Execute tool in the Openowl MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on stop_watcher? +

Register the Openowl MCP server in PolicyLayer and add a rule for stop_watcher: 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 Openowl. Nothing to install.

What risk level is stop_watcher? +

stop_watcher is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit stop_watcher? +

Yes. Add a rate_limit block to the stop_watcher 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 stop_watcher completely? +

Set action: deny in the PolicyLayer policy for stop_watcher. 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 stop_watcher? +

stop_watcher is provided by the Openowl MCP server (mihir-kanzariya/openowl). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Openowl tool call.

Start from Openowl, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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40 Openowl tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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