DebuggAI

DebuggAI super‑charges engineers with an AI‑powered application‑monitoring platform that finds and fixes bugs while your app runs locally, in production, or in CI. Get deep contextual insights about how your app is performing, how it's being used, and where the problems are.

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✨ Why DebuggAI?

Most AI coding tools focus on writing code.
DebuggAI focuses on the other 50 % of an engineer’s life: getting it to run.

• 1‑line monitoring SDK — drop‑in client (Node, Python, Go) that captures rich runtime context remotely similar to Sentry or Datadog
• AI Debug Chat — ask “Why is this KeyError happening?” and get a pinpointed answer with links to the offending lines
• Instant Fix Suggestions — one‑click patches and PRs generated from stack‑trace + context
• Source‑map de‑minification — readable traces even for bundled / minified front‑end code
• Branch‑aware log search — slice errors by branch, release, or feature flag to zero in fast
• Works anywhere you code — VS Code, JetBrains IDEs, or CLI

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📺 Demo - Get Instant Insight Into Runtime Issues

🔍 Typical workflows:

1. You use your favorite AI agent to write code
2. You run your app and it crashes (ah whyyyyy!)
3. DebuggAI sees the error, grabs the full stack trace + context, and uses it to generate a solution & show you EXACTLY where to look
4. You review the solution, edit it locally if needed, and apply it

🔍 How it works

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🖥️ Core IDE Features

Feature	Description	Demo
AI Debug Chat	Conversational agent with full stack context
Inline Fix Suggestions	Autocomplete patches directly in diff‑view
Code Edit Commands	Select > “Improve error handling” to refactor
Debug Actions	One‑click shortcuts: Explain Trace, Add Test, Generate Fix PR

(GIFs borrowed from Continue until we finish recording DebuggAI‑specific demos.)

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🚀 Getting Started

1. Install the extension

   • VS Code Marketplace
   • Jetbrains coming soon

2. Create a project

   • Sign up & create a project in the DebuggAI app

     

3. Add the SDK (npm, pip, etc.)

   # Node
   npm i debugg-ai-sdk
   
   # Python
   pip install debugg-ai-sdk

4. Initialize (one line):

   • Get the initizalization code from the DebuggAI app

     

   • Initialize the SDK

     // index.ts
     import { DebuggAiLogger } from "debugg-ai-sdk";
     const logger = new DebuggAiLogger({ projectKey: "<YOUR_KEY>" });

5. Trigger an error – head back to the IDE and watch DebuggAI suggest a fix ⚡

Full walkthrough ▶ docs.debugg.ai/getting-started

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🛠️ Configuration

You can login to your DebuggAI account directly in the extension and then it will automatically connect to your project.

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🤝  Interested in Contributing?

We're looking to expand the DebuggAI team!

If you're interested in joining the team or contributing to the project, please reach out to us at hello@debugg.ai.

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📜 License & Credits

• Code: Apache 2.0 © 2025 Debugg, Inc.
• Foundation: proudly built on Continue

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Attribution

We at Debugg AI would like to thank the Continue team for their work on this extension. Their extensive code base provided an excellent starting point for this extension. You can find the original repository here.

Debugg AI aims to give local AI coding agents more context and awareness of runtime events through system wide application monitoring and as such is not focused on developing the extensive feature set of Continue. If you are looking for a great tool for developers to create, share, and use custom AI code assistants, we recommend checking out Continue.

A copy of the original license is included in this repository for your convenience. We have used best efforts to ensure that the original license is respected. If you have any questions, please contact us at support@debugg.ai.

Original License

Apache 2.0 © 2023-2024 Continue Dev, Inc.

_{Made with ❤️ and too many stack traces in San Francisco.}