jamesmurdza/awesome-ai-devtools

★ 3,786Audience · developerComplexity · 1/5Setup · easy

Mindmap

mindmap
  root((AI Devtools))
    IDEs
      AI-native editors
      VS Code forks
    Extensions
      GitHub Copilot
      Autocomplete tools
    Automated Bots
      PR reviewers
      CI/CD tools
    Agent Tools
      Orchestration
      Sandboxing

mindmap root((AI Devtools)) IDEs AI-native editors VS Code forks Extensions GitHub Copilot Autocomplete tools Automated Bots PR reviewers CI/CD tools Agent Tools Orchestration Sandboxing

Click or tap to explore — scroll the page freely

Things people build with this

USE CASE 1

Find the right AI coding extension to add to VS Code or another editor without researching dozens of options manually.

USE CASE 2

Discover tools that automate code review and pull request comments in your CI/CD workflow.

USE CASE 3

Browse AI-native IDEs like Cursor or Windsurf to find a smarter alternative to your current editor.

USE CASE 4

Explore agent infrastructure tools for building AI-powered developer products.

Getting it running

Difficulty · easy Time to first run · 5min

In plain English

awesome-ai-devtools is a curated directory of tools that use AI to assist software developers. The list is organized into roughly a dozen categories, covering everything from code editors to automated bots that participate in the software development process. The development environments section covers two kinds of tools: AI-native IDEs (complete coding environments built with AI as a core feature, such as Cursor and Windsurf, both of which are forks of VS Code) and IDE extensions (plugins that add AI capabilities to editors developers already use, like GitHub Copilot, Cline, Continue, Tabnine, and Amazon Q Developer). The extensions vary in what they offer, from simple autocomplete to agents that can create files, run commands, and browse the web on the developer's behalf. Other categories include terminal agents and CLI utilities, web-based coding tools such as app builders and UI generators, and desktop and mobile applications. An automated workflows section covers bots that participate in the pull request and code review process as well as tools that run during CI/CD pipelines to automate testing and quality checks. The list also covers agent infrastructure: tools for orchestrating multiple AI agents together, sandboxing agent actions so they cannot cause unintended side effects, managing configuration and context, and tracking token usage and API costs. A specialized tools section adds git commit helpers, documentation generators, and code search tools. The repository is a community resource maintained through GitHub pull requests. Contribution guidelines specify which tools qualify for inclusion. No single vendor or product is promoted over others, the list is descriptive rather than ranked. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1

Based on awesome-ai-devtools, which AI IDE extension is best for someone who wants an agent that can create files and run terminal commands automatically?

Prompt 2

From the awesome-ai-devtools directory, list the tools in the automated-workflows category that integrate with GitHub pull requests.

Prompt 3

I use VS Code, based on awesome-ai-devtools, which AI extensions should I consider and what makes each one different?

Prompt 4

Using awesome-ai-devtools as a reference, compare the AI-native IDEs listed and explain their main differences.

Prompt 5

Find tools in awesome-ai-devtools that help track token usage and API costs when building AI apps.

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