debugpy_session_start · Debugpy MCP: Risk & Policy

WHAT IT DOES

What debugpy_session_start does on Debugpy

AI agents invoke debugpy_session_start 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_start needs a policy

Based on the server context, this tool likely initiates a debug session by attaching a debugger to a running Python process inside a Docker container. This constitutes an Execute-level action as it triggers an external operation (process injection/attachment).

From the tool's definition Tool name 'debugpy_session_start' on a server described as enabling agents to attach debugpy to running Python processes and inject into processes; description is empty and uninformative.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

debugpy_session_start Rate-limited

debugpy_session_start 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_start": {
      "limits": [
        {
          "counter": "debugpy_session_start_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_start

What does the debugpy_session_start tool do? +

debugpy_session_start. 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_start? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_session_start: 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_start? +

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

Can I rate-limit debugpy_session_start? +

Yes. Add a rate_limit block to the debugpy_session_start 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_start completely? +

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

debugpy_session_start 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.