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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
AI app builder turning English prompts into full-stack apps with provisioned DB, auth and hosting; also hosts autonomous agents.
No public pricing
No public pricing
No public pricing
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Natural-language full-stack app generation
- ✦Auto-provisioned Postgres, auth, storage and hosting
- ✦Full code ownership with GitHub export
- ✦Managed hosting for autonomous AI agents
- ✦200+ bundled AI models
- ✦MCP and CLI tooling
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Ship a SaaS without an engineering team
- →Build internal tools from a description
- →Deploy always-on AI agents quickly
- →Provide infra for AI-coded apps