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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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GitLoop
✓ verifiedFree trial
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
👁 11K/mo♥ 2.7K
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Runcell - Jupyter AI Agent
✓ verifiedFreemium
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
👁 170K/mo♥ 5.5K
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Spellbox AI
✓ verifiedPaid
Desktop and VS Code AI coding assistant that generates and explains code from plain-language prompts, for developers and coding students.
♥ 15K
Pricing
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
1-year license: $40 (early-bird price, normally $65)
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
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- ✦AI code generation from natural-language prompts
- ✦AI code explanation for unfamiliar snippets
- ✦Snippet bookmarking for later reuse
- ✦VS Code extension integration
- ✦Support for major programming languages
- ✦Desktop apps for Windows and macOS
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
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- →Speeding up debugging and syntax lookup for professional developers
- →Helping students understand coding concepts step by step
- →Generating boilerplate or algorithmic code snippets
- →Saving and organizing reusable code snippets across projects
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