debugpy_threads

List active threads and stack frames. Stopped threads include full stack traces.

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

What debugpy_threads does on Debugpy

AI agents call debugpy_threads 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_threads needs a policy

This tool retrieves runtime state information about threads and their stack frames from a debugged Python process. While the information disclosed could be sensitive (internal execution state, variable contents in stack frames), the operation itself is read-only with no side effects or reversible/irreversible modifications.

From the tool's definition Tool description states it 'List[s] active threads and stack frames' - a query operation that retrieves debugging state information without modifying it. The word 'list' and 'stack traces' confirm this is introspection/retrieval only.

Questions about debugpy_threads

What does the debugpy_threads tool do? +

List active threads and stack frames. Stopped threads include full stack traces. 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_threads? +

Register the Debugpy MCP server in PolicyLayer and add a rule for debugpy_threads: 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_threads? +

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

Can I rate-limit debugpy_threads? +

Yes. Add a rate_limit block to the debugpy_threads 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_threads completely? +

Set action: deny in the PolicyLayer policy for debugpy_threads. 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_threads? +

debugpy_threads 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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