Show HN: VibeDbg – Cconversational, LLM-Powered AI Assistant for WinDbg (github.com)

VibeDbg is a new conversational, LLM-powered assistant that layers natural-language interaction on top of WinDbg, turning command-line debugging into an interactive chat-style experience. It ships as a native WinDbg extension (example: .load C:\github\VibeDbg\ext\bin\x64\Release\VibeDbg.dll) and connects to a Model Context Protocol (MCP) server over a named pipe to translate user intent into WinDbg commands, explain results, and suggest next steps. Out-of-the-box features include LLM-driven command execution and explanations, session management, live feedback during debugging and crash-dump analysis, integration with existing WinDbg extensions and custom workflows, and helper commands like !vibedbg_help, !vibedbg_connect and !vibedbg_status. Technically, VibeDbg supports the full range of standard WinDbg operations (breakpoints, memory displays, stack ops, stepping) and enhances dx-based object visualization using NatVis: object formatting, grid/tabular views, recursive expansion, format specifiers and verbose output. The project provides an MCP server implementation (configurable via a VS Code mcp.json example) and recommends starting WindbgX, loading the extension, launching the named-pipe server and then the MCP server. For practitioners this promises faster onboarding, richer introspection and tighter LLM-assisted workflows, though it also raises operational concerns around correctness, command safety and trust boundaries when allowing an LLM to execute debugger actions.