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AI-powered IDE with code completion, generation, explanation and debugging, plus a cloud dev environment, for developers.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
An on-device developer memory tool that auto-captures code, docs and context across apps so engineers can search and reuse it later.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Design-system platform that packages tokens, code components, and rules into scoped context for AI coding agents.
No public pricing
No public pricing
No public pricing
- ✦AI code completion and snippet generation
- ✦Natural-language code generation
- ✦Code explanation and AI Q&A
- ✦Automated bug detection and fixes
- ✦Zero-config cloud development environment
- ✦Project creation from templates or Git
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Automatic capture of code, docs and context across apps
- ✦Long-term memory engine for time-based search of past work
- ✦One-click save, search and AI-tagging of code snippets
- ✦Local, on-device processing with optional cloud sync
- ✦Plugin support for browsers and IDEs like VS Code
- ✦MCP integration with external LLMs for contextual answers
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Scoped MCP context distribution to multiple AI coding tools
- ✦Design token and component API management
- ✦Collaborative documentation with analytics
- ✦Figma and Storybook data source integration
- ✦Feedback loop for improving AI context quality
- ✦Skill and exporter management for agent capabilities
- →Writing and completing code faster with AI
- →Onboarding to unfamiliar codebases
- →Debugging and optimizing code
- →Spinning up dev environments in the browser
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Recalling code snippets and context from past coding sessions
- →Feeding accurate personal context into AI coding assistants
- →Keeping research notes and links without manual bookmarking
- →Preserving shared context across team collaboration tools
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Product teams giving AI coding agents accurate design-system context
- →Design system managers publishing a single source of truth
- →Engineering teams reducing token usage by scoping agent context per team