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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
AI coding assistant for editors and IDEs that explains, refactors, documents, and generates code across 56 languages.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
- ✦Bug detection and fix suggestions
- ✦Code and CSS framework conversion
- ✦Unit test and documentation generation
- ✦Regex, SQL query, and CI/CD pipeline generation
- ✦Code explanation and style checking
- ✦Editor extensions for VS Code, Sublime, JetBrains, Visual Studio
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
- →Generating unit tests for existing functions
- →Refactoring legacy code to modern practices
- →Producing inline documentation automatically
- →Learning new programming languages or concepts via AI explanations
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags