debugpy_session_stop · Debugpy MCP: Risk & Policy

WHAT IT DOES

What debugpy_session_stop does on Debugpy

AI agents invoke debugpy_session_stop 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_session_stop needs a policy

This tool executes a command to stop an active debugging session. While it does not terminate the debuggee process or destructively delete data, it actively triggers an external operation whose consequences are non-trivial: it interrupts debugging activity and disconnects from a running process.

From the tool's definition Tool name and description: 'debugpy_session_stop' - 'Cleanly disconnect the DAP session.' This triggers an external operation (disconnection of a Debug Adapter Protocol session) that affects a running Python debugger process within a Docker container.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

debugpy_session_stop Rate-limited

debugpy_session_stop 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_session_stop": {
      "limits": [
        {
          "counter": "debugpy_session_stop_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_session_stop

What does the debugpy_session_stop tool do? +

Cleanly disconnect the DAP session. Does not terminate the debuggee. 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_session_stop? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_session_stop: 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_session_stop? +

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

Can I rate-limit debugpy_session_stop? +

Yes. Add a rate_limit block to the debugpy_session_stop 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_session_stop completely? +

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

debugpy_session_stop 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.