base on 🧙 Build, run, and manage data pipelines for integrating and transforming data. # Mage OSS ### Build modern data pipelines locally — fast, visual, and production-ready. <br /> Mage OSS is a self-hosted development environment designed to help teams create production-grade data pipelines with confidence. Ideal for automating ETL tasks, architecting data flow, or orchestrating transformations — all in a fast, notebook-style interface powered by modular code. When it’s time to scale, [Mage Pro](https://mage.ai) — our core platform — unlocks enterprise orchestration, collaboration, and AI-powered workflows. <br /> <a href="https://mage.ai"><img alt="Mage AI GitHub repo stars" src="https://img.shields.io/github/stars/mage-ai/mage-ai?style=for-the-badge&logo=github&labelColor=000000&logoColor=FFFFFF&label=stars&color=0500ff" /></a> <a href="https://hub.docker.com/r/mageai/mageai"><img alt="Mage AI Docker downloads" src="https://img.shields.io/docker/pulls/mageai/mageai?style=for-the-badge&logo=docker&labelColor=000000&logoColor=FFFFFF&label=pulls&color=6A35FF" /></a> <a href="https://github.com/mage-ai/mage-ai/blob/master/LICENSE"><img alt="Mage AI license" src="https://img.shields.io/github/license/mage-ai/mage-ai?style=for-the-badge&logo=codeigniter&labelColor=000000&logoColor=FFFFFF&label=license&color=FFCC19" /></a> <a href="https://www.mage.ai/chat"><img alt="Join the Mage AI community" src="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" /></a> <br /> ## What you can do with Mage OSS - Build pipelines locally with Python, SQL, or R in a modular notebook-style UI - Run jobs manually or on a schedule (cron supported) - Connect to databases, APIs, and cloud storage with prebuilt connectors - Debug visually with logs, live previews, and step-by-step execution - Set up quickly with Docker, pip, or conda — no cloud account required - Your go-to workspace for local pipeline development — fully in your control. <img width="100%" alt="mage" src="https://github.com/user-attachments/assets/75992872-20a6-4120-8bf0-9c22a3d66450" /> <br /><br /> ## Start local. Scale when you're ready. Use 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. [**Try Mage Pro free →**](https://mage.ai) <br /> ### Quickstart Install using Docker (recommended): ```bash docker pull mageai/mageai:latest ``` Or with pip: ```bash pip install mage-ai ``` Or with conda: ```bash conda install -c conda-forge mage-ai ``` Full setup guide and docs: [docs.mage.ai](https://docs.mage.ai/getting-started/setup#%E2%9B%B5%EF%B8%8F-mage-oss-overview) <br /> ## Core Features | Feature | Description | | :- | :- | | Modular pipelines | Build pipelines block-by-block using Python, SQL, or R | | Notebook UI | Interactive editor for writing and documenting logic | | Data integrations | Prebuilt connectors to databases, APIs, and cloud storage | | Scheduling | Trigger pipelines manually or on a schedule | | Visual debugging | Step-by-step logs, data previews, and error handling | | dbt support | Build and run dbt models directly inside Mage | <br /> ## Example Use Cases - Move data from Google Sheets to Snowflake with a Python transform - Schedule a daily SQL pipeline to clean and aggregate product data - Develop dbt models in a visual notebook-style interface - Run simple ETL/ELT jobs locally with full transparency <br /> ## Documentation Looking for how-to guides, examples, or advanced configuration? Explore our full documentation at [docs.mage.ai](https://docs.mage.ai). <br /> ## Contributing We welcome contributions of all kinds — bug fixes, docs, new features, or community examples. Start with our [contributing guide](https://docs.mage.ai/contributing/overview), check out open issues, or suggest improvements. <br /> ## Ready to scale? Mage Pro has you covered. Mage Pro is a powered-up platform built for teams. It adds everything you need for production pipelines, at scale. - Magical AI-assisted development and debugging - Multi-environment orchestration - Role-based access control - Real-time monitoring & alerts - Powerful CI/CD & version control - Powerful enterprise features - Available fully managed, hybrid, or on-premises [**Try Mage Pro free →**](https://mage.ai) ", Assign "at most 3 tags" to the expected json: {"id":"7871","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"