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Software Development__code Generation__sql Query GenerationAI Agents Infrastructure__ai Agents__coding AgentsSoftware Development__coding Assistants Copilots__ide CopilotsSoftware Development__coding Assistants CopilotsSoftware Development__code GenerationAI Agents Infrastructure__ai AgentsSoftware DevelopmentAI Agents Infrastructure
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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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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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Open Source Database Designs
✓ verifiedFreemium
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
👁 27K/mo
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦Natural language to SQL conversion
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
Use cases
- →Generating SQL queries from text descriptions.
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →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
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
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