stop_running_timer · Clockify Time Tracking MCP

WHAT IT DOES

What stop_running_timer does on Clockify Time Tracking

AI agents invoke stop_running_timer to trigger actions in Clockify Time Tracking. 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 IT NEEDS A POLICY

Why stop_running_timer needs a policy

This tool executes an action that changes the state of a running timer. Unlike Read tools (which only retrieve data), this modifies application state. It's not Destructive since stopping a timer doesn't irreversibly delete data and can be reversed by restarting. It's not Financial or Write (data creation) in the typical sense.

From the tool's definition Tool name 'stop_running_timer' indicates it performs an action that controls or modifies an active timer state. While the description is empty, the semantic meaning of 'stop' implies execution of an operation with side effects on a running process.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

stop_running_timer Rate-limited

stop_running_timer 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.

View as policy code

policy.json

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

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Clockify Time Tracking, so you can run agents against it safely.

FAQ

Questions about stop_running_timer

What does the stop_running_timer tool do? +

stop_running_timer. It is categorised as a Execute tool in the Clockify Time Tracking 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_running_timer? +

Register the Clockify Time Tracking MCP server in PolicyLayer and add a rule for stop_running_timer: 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 Clockify Time Tracking. Nothing to install.

What risk level is stop_running_timer? +

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

Can I rate-limit stop_running_timer? +

Yes. Add a rate_limit block to the stop_running_timer 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_running_timer completely? +

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

stop_running_timer is provided by the Clockify Time Tracking MCP server (pypi:clockify-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.