{"data":{"slug":"mage-ai-mage-ai","name":"mage-ai","tagline":"π§ Build, run, and manage data pipelines for integrating and transforming data.","github_url":"https://github.com/mage-ai/mage-ai","owner":"mage-ai","repo":"mage-ai","owner_avatar_url":"https://avatars.githubusercontent.com/u/69371472?v=4","primary_language":"Python","stars":8770,"forks":978,"topics":["artificial-intelligence","data","data-engineering","data-integration","data-pipelines","data-science","dbt","elt","etl","machine-learning","orchestration","pipeline","pipelines","python","reverse-etl","spark","sql","transformation"],"archived":false,"github_pushed_at":"2026-07-02T22:39:30+00:00","maintenance_label":"Active","url":"https://www.graphcanon.com/tools/mage-ai-mage-ai","markdown_url":"https://www.graphcanon.com/tools/mage-ai-mage-ai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/mage-ai-mage-ai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=mage-ai-mage-ai","description":"π§ Build, run, and manage data pipelines for integrating and transforming data.","homepage_url":"https://www.mage.ai","license":"Apache-2.0","open_issues":617,"watchers":60,"ai_summary":null,"readme_excerpt":"# Mage OSS\n\n### Build modern data pipelines locally β fast, visual, and production-ready.\n\n
\n\nMage OSS is a self-hosted development environment designed to help teams create production-grade data pipelines with confidence.\n\nIdeal for automating ETL tasks, architecting data flow, or orchestrating transformations β all in a fast, notebook-style interface powered by modular code.\n\nWhen itβs time to scale, [Mage Pro](https://mage.ai) β our core platform β unlocks enterprise orchestration, collaboration, and AI-powered workflows.\n\n
\n\n![\"Mage](\"https://img.shields.io/github/stars/mage-ai/mage-ai?style=for-the-badge&logo=github&labelColor=000000&logoColor=FFFFFF&label=stars&color=0500ff\")
\n![\"Mage](\"https://img.shields.io/docker/pulls/mageai/mageai?style=for-the-badge&logo=docker&labelColor=000000&logoColor=FFFFFF&label=pulls&color=6A35FF\")
\n![\"Mage](\"https://img.shields.io/github/license/mage-ai/mage-ai?style=for-the-badge&logo=codeigniter&labelColor=000000&logoColor=FFFFFF&label=license&color=FFCC19\")
\n![\"Join](\"https://img.shields.io/badge/Join%20the%20community-black.svg?style=for-the-badge&logo=lightning&labelColor=000000&logoColor=FFFFFF&label=&color=DD55FF&logoWidth=20\")
\n\n
\n\n## What you can do with Mage OSS\n\n- Build pipelines locally with Python, SQL, or R in a modular notebook-style UI\n\n- Run jobs manually or on a schedule (cron supported)\n\n- Connect to databases, APIs, and cloud storage with prebuilt connectors\n\n- Debug visually with logs, live previews, and step-by-step execution\n\n- Set up quickly with Docker, pip, or conda β no cloud account required\n\n- Your go-to workspace for local pipeline development β fully in your control.\n \n![\"mage\"](\"https://github.com/user-attachments/assets/75992872-20a6-4120-8bf0-9c22a3d66450\")
\n\n\n
\n\n## Start local. Scale when you're ready.\n\nUse Mage OSS to build and run pipelines on your machine. When you're ready for advanced tooling, performance, and AI-assisted productivity, Mage Pro is just one click away.\n\n[**Try Mage Pro free β**](https://mage.ai)\n\n
\n\n### Quickstart\n\nInstall using Docker (recommended):\n\n```bash\ndocker pull mageai/mageai:latest\n```\n\nOr with pip:\n\n```bash\npip install mage-ai\n```\n\nOr with conda:\n\n```bash\nconda install -c conda-forge mage-ai\n```\n\nFull setup guide and docs: [docs.mage.ai](https://docs.mage.ai/getting-started/setup#%E2%9B%B5%EF%B8%8F-mage-oss-overview)\n\n
\n\n## Core Features\n\n| Feature | Description |\n| :- | :- |\n| Modular pipelines | Build pipelines block-by-block using Python, SQL, or R |\n| Notebook UI | Interactive editor for writing and documenting logic |\n| Data integrations | Prebuilt connectors to databases, APIs, and cloud storage |\n| Scheduling | Trigger pipelines manually or on a schedule |\n| Visual debugging | Step-by-step logs, data previews, and error handling |\n| dbt support | Build and run dbt models directly inside Mage |\n\n
\n\n## Example Use Cases\n\n- Move data from Google Sheets to Snowflake with a Python transform\n- Schedule a daily SQL pipeline to clean and aggregate product data\n- Develop dbt models in a visual notebook-style interface\n- Run simple ETL/ELT jobs locally with full transparency\n\n
\n\n## Documentation\n\nLooking for how-to guides, examples, or advanced configuration?\n\nExplore our full documentation at [docs.mage.ai](https://docs.mage.ai).\n\n\n
\n\n## Contributing\n\nWe welcome contributions of all kinds β bug fixes, docs, new features, or community examples.\n\nStart with our [contributing guide](https://docs.mage.ai/contributing/overview), check out open issues, or suggest improvements.\n\n
\n\n## Ready to scale? Mage Pro has you covered.\n\nMage Pro is a powere","github_created_at":"2022-05-16T22:11:39+00:00","created_at":"2026-07-15T10:50:18.541525+00:00","updated_at":"2026-07-15T10:50:23.575544+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"data","name":"data"},{"slug":"data-engineering","name":"data-engineering"},{"slug":"data-integration","name":"data-integration"},{"slug":"data-pipelines","name":"data-pipelines"},{"slug":"data-science","name":"data-science"},{"slug":"dbt","name":"dbt"},{"slug":"elt","name":"elt"}],"trust":{"provenance":{"is_fork":false,"github_id":493014338,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-15T10:50:20.258Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":12,"last_release_at":"2026-01-21T17:32:41Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":207,"high_count":0,"last_scan_at":"2026-07-15T10:50:20.698Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-15T10:50:20.026Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-07-15T10:50:20.026Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-15T10:50:20.026Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-07-15T10:50:20.026Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-15T10:50:20.026Z"}}}}