debugpy_list_containers

debugpy_list_containers

Server Debugpy will-garrett/debugpy-mcp
Category Read
Risk class Low
Parameters 00 required

What debugpy_list_containers does on Debugpy

AI agents call debugpy_list_containers to retrieve information from Debugpy without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why debugpy_list_containers needs a policy

This tool retrieves information about containers (a read operation with no side effects). However, the severity is elevated to 'medium' rather than 'low' because exposing container inventory to an AI agent could reveal sensitive infrastructure details, enable targeting of specific services for exploitation, or expose private container configurations—allowing an attacker to map the deployment landscape before…

From the tool's definition Tool name 'debugpy_list_containers' indicates a listing/discovery operation. Within a debugger MCP server context, listing containers retrieves metadata about running Docker containers without modifying them.

Questions about debugpy_list_containers

What does the debugpy_list_containers tool do? +

debugpy_list_containers. It is categorised as a Read tool in the Debugpy MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on debugpy_list_containers? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_list_containers: 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_list_containers? +

debugpy_list_containers is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit debugpy_list_containers? +

Yes. Add a rate_limit block to the debugpy_list_containers 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_list_containers completely? +

Set action: deny in the PolicyLayer policy for debugpy_list_containers. 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_list_containers? +

debugpy_list_containers 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.

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