Stop the current debug target and clear the debug session.
AI agents invoke stop to trigger actions in Mcp Debugger Node. 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.
Although 'stop' does not delete persistent data, it terminates an active external process and clears session state, making it an Execute-category action. The severity is high because stopping a debug target could interrupt critical application execution or debugging workflows, with moderate blast radius if invoked by a misaligned agent.
From the tool's definition Tool 'stop' stops the current debug target and clears the debug session. This terminates an external process (Node.js debugger) and modifies the debug state irreversibly for that session.
Documented attack patterns abuse exactly the kind of access stop gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Debugger Node, and nothing reaches the server without passing your rules. This is the rule we recommend for stop:
{
"version": "1",
"default": "deny",
"tools": {
"stop": {
"limits": [
{
"counter": "stop_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} 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.
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Stop the current debug target and clear the debug session. It is categorised as a Execute tool in the Mcp Debugger Node MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Debugger Node MCP server in PolicyLayer and add a rule for 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 Mcp Debugger Node. Nothing to install.
stop 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 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.
Set action: deny in the PolicyLayer policy for 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.
stop is provided by the Mcp Debugger Node MCP server (mohammed-almassri/mcp-debugger-node). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mcp Debugger Node, 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.
11 Mcp Debugger Node tools catalogued and risk-classified — across an index of 43,000+ MCP servers.