Overview

Claude Debugs For You is an MCP server that transforms a conventional IDE debugger into a conversational partner. By exposing the debugger’s console and expression evaluation as an interactive chat interface, it lets language‑model assistants—such as Claude Desktop or Continue—inspect program state, set breakpoints, and run code snippets in real time. This removes the need to manually copy stack traces or debug output into the model, allowing the assistant to reason about and manipulate the running program directly.

The server is language‑agnostic: it only requires that the target environment supports a debugger console and has a valid configuration in VS Code. Once the MCP server is running, any MCP‑compatible client can send commands to evaluate expressions or control the debug session. The model can ask for the value of a variable, modify a local, or step through code—all while keeping the context of the conversation. This tight coupling between AI reasoning and live debugging streamlines problem‑solving workflows, especially for complex or unfamiliar codebases.

Key capabilities include:

• Interactive expression evaluation – the assistant can request and receive the value of any variable or expression without leaving the chat.
• Breakpoint management – breakpoints can be added, removed, or listed through natural language commands.
• Step control – the model can instruct the debugger to step over, into, or out of code, and then immediately review the new state.
• Cross‑model support – although demonstrated with Claude Desktop, any MCP client (e.g., Continue, Cursor) can leverage the same server by pointing to its stdio or SSE endpoint.

Typical use cases involve debugging legacy code, troubleshooting unexpected runtime behavior, or teaching newcomers how to debug. A developer can ask the assistant “Why is undefined after this call?” and the model will evaluate the expression, report the result, and suggest fixes—all within a single conversation. In research settings, the server enables automated debugging pipelines where an AI iteratively refines code based on live feedback.

Integrating the server into existing workflows is straightforward: install the VS Code extension, copy the MCP endpoint (stdio or SSE) into your client’s configuration, and start a debugging session. The assistant then gains direct access to the program’s runtime environment without manual data extraction, making debugging faster, more accurate, and conversational.