stop_watcher · Python Codebase Analysis RAG System MCP

WHAT IT DOES

What stop_watcher does on Python Codebase Analysis RAG System

AI agents invoke stop_watcher to trigger actions in Python Codebase Analysis RAG System. 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_watcher needs a policy

This tool stops a running background process (file watcher). It triggers an external operation (process termination) whose effects depend on which codebase is specified. It is not purely read-only, nor does it delete data, but it does halt an ongoing system operation. Misuse could cause a codebase to no longer be monitored for changes, potentially causing stale data in the RAG system.

From the tool's definition 'Stops the file watcher for the specified codebase' — terminates an active monitoring/watching process

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

stop_watcher Rate-limited

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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "stop_watcher": {
      "limits": [
        {
          "counter": "stop_watcher_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 Python Codebase Analysis RAG System, so you can run agents against it safely.

FAQ

Questions about stop_watcher

What does the stop_watcher tool do? +

Stops the file watcher for the specified codebase. It is categorised as a Execute tool in the Python Codebase Analysis RAG System 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 Python Codebase Analysis RAG System 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 Python Codebase Analysis RAG System. 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 Python Codebase Analysis RAG System MCP server (shervinemp/codebasemcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.