debugpy_variables

Inspect variables in a stopped frame.

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

What debugpy_variables does on Debugpy

AI agents call debugpy_variables 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_variables needs a policy

This tool performs inspection/querying of variable values during debug sessions. While it is Read category (no side effects), severity is medium rather than low because variable inspection during debugging can expose sensitive information (credentials, tokens, personal data) that might be present in memory, creating a potential information disclosure risk if an AI agent misuses it to extract secrets from a running…

From the tool's definition Tool name 'debugpy_variables' and description 'Inspect variables in a stopped frame' indicate a read-only operation that retrieves variable state from a debugging session without modifying code, data, or program state.

Questions about debugpy_variables

What does the debugpy_variables tool do? +

Inspect variables in a stopped frame. 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_variables? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_variables: 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_variables? +

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

Can I rate-limit debugpy_variables? +

Yes. Add a rate_limit block to the debugpy_variables 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_variables completely? +

Set action: deny in the PolicyLayer policy for debugpy_variables. 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_variables? +

debugpy_variables 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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