Wait for a specific DAP event (e.g., 'stopped').
AI agents invoke dap_wait_for_event to trigger actions in Mcp 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.
This is an Execute tool because it waits for and reacts to debugger events during active debugging sessions, which constitutes triggering external operations (the debugger). While it does not directly execute Python code, it coordinates debugger state transitions and event handling—a form of execution control.
From the tool's definition Tool uses DAP (Debug Adapter Protocol) to wait for debugger events like 'stopped'. The sibling tools include dap_launch, dap_continue, dap_step_in, dap_step_out, dap_set_breakpoints—all indicative of active code execution and debugging control.
Documented attack patterns abuse exactly the kind of access dap_wait_for_event gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Debugpy, and nothing reaches the server without passing your rules. This is the rule we recommend for dap_wait_for_event:
{
"version": "1",
"default": "deny",
"tools": {
"dap_wait_for_event": {
"limits": [
{
"counter": "dap_wait_for_event_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}dap_wait_for_event 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.
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Wait for a specific DAP event (e.g., 'stopped'). It is categorised as a Execute tool in the Mcp Debugpy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Debugpy MCP server in PolicyLayer and add a rule for dap_wait_for_event: 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 Mcp Debugpy. Nothing to install.
dap_wait_for_event is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the dap_wait_for_event 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.
Set action: deny in the PolicyLayer policy for dap_wait_for_event. 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.
dap_wait_for_event is provided by the Mcp Debugpy MCP server (markomanninen/mcp-debugpy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Debugpy, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
16 Mcp Debugpy tools catalogued and risk-classified — across an index of 43,000+ MCP servers.