debugpy_pause · Debugpy MCP: Risk & Policy

WHAT IT DOES

What debugpy_pause does on Debugpy

AI agents invoke debugpy_pause to trigger actions in Debugpy. 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 debugpy_pause needs a policy

This tool pauses execution of running threads in a Python process inside a Docker container. It directly controls process execution state, which is an external operational effect. Misuse could halt production services or cause deadlocks/timeouts, making the blast radius high.

From the tool's definition Pause execution. Defaults to all threads.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

debugpy_pause Rate-limited

debugpy_pause 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": {
    "debugpy_pause": {
      "limits": [
        {
          "counter": "debugpy_pause_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 Debugpy, so you can run agents against it safely.

FAQ

Questions about debugpy_pause

What does the debugpy_pause tool do? +

Pause execution. Defaults to all threads. It is categorised as a Execute tool in the Debugpy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on debugpy_pause? +

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

What risk level is debugpy_pause? +

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

Can I rate-limit debugpy_pause? +

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

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

debugpy_pause is provided by the Debugpy MCP server (will-garrett/debugpy-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.