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IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Open-source, self-hostable AI coding agent with autocomplete, in-IDE chat and autonomous task execution for teams needing data control.
AI-powered code editor with agentic workflows for developers.
No public pricing
No public pricing
No public pricing
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦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
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Autonomous AI agent that plans and executes multi-step coding tasks
- ✦In-IDE chat for asking, editing, debugging and generating code
- ✦Real-time code autocompletion using retrieval-augmented generation
- ✦Repository search and analysis for context-aware execution
- ✦Integrations with GitHub, databases and CI/CD pipelines
- ✦Self-hosted/on-premise deployment option for data privacy
- ✦Support for choosing among different underlying LLMs
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →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
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Developer teams wanting an in-IDE autonomous coding agent
- →Organizations requiring on-premise/self-hosted AI coding tools for data control
- →Individuals doing 'vibe coding' with minimal manual coding
- →Teams fine-tuning an AI assistant to their own codebase
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow