# Mage — developer ecosystem report

> Magical tools for data.

- GitHub org: `mage-ai`
- Category: ai
- Overall score: 40.0 / 100
- Overall rank: #455
- Last refreshed: 2026-08-14

## Pillar scores

| Pillar | Score / 100 | Rank | Weight in overall |
| --- | --- | --- | --- |
| Code & Polish | 34.0 | #900 | ~22% |
| Education | 67.0 | #395 | ~18% |
| AI readiness | 41.0 | #312 | part of Reach |
| Builder experience | 0.0 | #1 | ~12% |
| Community | 36.0 | #427 | ~16% |
| Reach | 71.0 | #63 | ~18% |
| Momentum | 13.0 | #727 | ~14% |

## Links

- GitHub: https://github.com/mage-ai
- Website: https://www.mage.ai
- Docs: https://docs.mage.ai

## Public GitHub totals

| Metric | Value |
| --- | --- |
| Repos analyzed | 12 |
| Stars | 9,110 |
| Forks | 1,543 |
| Open issues | 701 |
| Contributors | — |

## Top repositories

| Repo | Stars | Language | Description |
| --- | --- | --- | --- |
| [mage-ai](https://github.com/mage-ai/mage-ai) | 8,798 | Python | 🧙 Build, run, and manage data pipelines for integrating and transforming data. |
| [mage-zoomcamp](https://github.com/mage-ai/mage-zoomcamp) | 104 | Dockerfile | This repository will contain all of the resources for the Mage component of the Data Engineering Zoomcamp: https://githu |
| [mage-ai-terraform-templates](https://github.com/mage-ai/mage-ai-terraform-templates) | 45 | HCL | Terraform templates for deploying mage-ai to AWS, GCP and Azure |
| [machine_learning](https://github.com/mage-ai/machine_learning) | 24 | Python | The definitive end-to-end machine learning (ML lifecycle) guide and tutorial for data engineers. |
| [mlops](https://github.com/mage-ai/mlops) | 22 | Python | — |
| [compose-quickstart](https://github.com/mage-ai/compose-quickstart) | 18 | Dockerfile | A quickstart repo for Mage using Docker compose. |
| [helm-charts](https://github.com/mage-ai/helm-charts) | 12 | Go Template | — |
| [magic-devcontainer](https://github.com/mage-ai/magic-devcontainer) | 12 | Python | A demo instance of mage for pulling sample data from a public Google pub/sub topic and transforming with dbt. |
| [dbt-quickstart](https://github.com/mage-ai/dbt-quickstart) | 8 | Python | — |
| [docker](https://github.com/mage-ai/docker) | 8 | Dockerfile | Dockerfile and Docker compose templates |
| [assets](https://github.com/mage-ai/assets) | 7 | — | Media assets used in repository documentation. |
| [llm_orchestration](https://github.com/mage-ai/llm_orchestration) | 7 | Python | — |

## Methodology

Scores are computed from public signals only (GitHub, package registries, docs sites, community platforms). Pillar definitions: https://www.smoower.com/docs.md

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