claude-debugs-for-you

📋 Overview:

The webpage is a GitHub repository for a VS Code extension and MCP (Model Context Protocol) server that enables Large Language Models (LLMs), such as Claude, to interactively debug code across various programming languages. The project is language-agnostic, relying on debugger console support and a valid launch.json file for debugging in VSCode.

⭐ Key Points:

• The repository provides a VS Code extension and MCP server for LLM-assisted debugging.


• It supports interactive debugging and expression evaluation.


• It is designed to be language-agnostic, working with any language supported by VS Code's debugger.


• The project is compatible with Claude and other LLMs, demonstrated with Claude Desktop.


• Instructions for getting started, contributing, and running examples are included.


• The project is under MIT license.


🔍 Main Findings:

• The core functionality allows LLMs to use debugging tools within VS Code, stepping through code and evaluating expressions to identify and resolve issues.


• Set-up involves downloading, installing the extension, configuring the node binary path, and setting up the MCP client.


• Two MCP methods are defined: node process based (recommended for Claude Desktop) and `/sse` based (Cursor).


• The project encourages contributions, with a list of potential enhancements provided.


📊 Details:

• The extension can be downloaded from the releases page or VS Code Marketplace.


• Configuration details are provided for integrating with Continue.dev.


• Configuration of port settings for both MCP server and VS Code extension, via environment variables and JSON settings, is described.


• A demonstration video illustrating the use of Claude Desktop for debugging is included.


• Information for package creation and running an example are described.


• The repository has 167 stars and 9 forks.


• The project is primarily written in TypeScript (93.6%) with a small portion in JavaScript (6.4%).

🎯 Conclusion:
The "claude-debugs-for-you" repository offers a framework to utilize LLMs in interactive code debugging within VS Code, fostering a language-agnostic approach through MCP. The project aims to streamline debugging, allowing AI models to step through code, evaluate expressions, and recommend fixes, thereby augmenting traditional debugging workflows.