debugpy_step_over · Debugpy MCP: Risk & Policy

WHAT IT DOES

What debugpy_step_over does on Debugpy

AI agents invoke debugpy_step_over 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_step_over needs a policy

This tool executes a debugger control action that advances execution in a running Python process. It triggers an external operation (DAP 'next' command) that changes the state of a live process, making it an Execute category action. Misuse could interfere with production processes running inside Docker containers.

From the tool's definition Step over the current line (DAP 'next')

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

debugpy_step_over Rate-limited

debugpy_step_over 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_step_over": {
      "limits": [
        {
          "counter": "debugpy_step_over_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_step_over

What does the debugpy_step_over tool do? +

Step over the current line (DAP 'next'). 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_step_over? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_step_over: 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_step_over? +

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

Can I rate-limit debugpy_step_over? +

Yes. Add a rate_limit block to the debugpy_step_over 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_step_over completely? +

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

debugpy_step_over 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.