debugpy_logs

debugpy_logs

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

What debugpy_logs does on Debugpy

AI agents call debugpy_logs 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_logs needs a policy

The tool name strongly suggests retrieving debug logs from a debugpy session, which is a read operation with no side effects. Logs are typically immutable historical data. While the empty description limits certainty, the naming convention and context of a debugger server (where log retrieval is non-destructive) support Read classification.

From the tool's definition Tool name 'debugpy_logs' with 'logs' suffix indicates log retrieval/querying. Description is empty, reducing confidence. Sibling tool 'debugpy_debugpy_logs' similarly suggests read-only log access.

Questions about debugpy_logs

What does the debugpy_logs tool do? +

debugpy_logs. 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_logs? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_logs: 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_logs? +

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

Can I rate-limit debugpy_logs? +

Yes. Add a rate_limit block to the debugpy_logs 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_logs completely? +

Set action: deny in the PolicyLayer policy for debugpy_logs. 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_logs? +

debugpy_logs 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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