# libmx3/mx3

a sample project showcasing/collecting cross platform techniques on mobile

Repository: https://github.com/libmx3/mx3
Canonical: https://ross.abutalabs.com/products/mx3
Language: C++
License: MIT
License Family: permissive
Last push: 2017-04-17T15:23:47+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4490, "days_push": 3425, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1159, forks 141 (observed 2026-08-28T04:03:48.540452+00:00)

## What it is
A sample C++ project demonstrating cross-platform mobile development techniques across Android, iOS, and Windows Phone using tools like Djinni and gyp. It also collects learning resources and tooling references for mobile C++ development.

## Use cases
- learn how to share C++ code between Android and iOS
- see an example of Djinni bindings for Java and Objective-C
- explore cross-platform mobile architecture techniques
- find resources on mobile C++ development
- set up a gyp-based multi-platform mobile build

## When to choose
- you want a reference example of sharing C++ code across mobile platforms
- you are researching Djinni or gyp-based mobile workflows

## When to avoid
- you need a maintained production-ready library
- you need Windows Phone support, which was never completed
- you want modern tooling - the project has not been updated since 2017

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: developer-tools, build-tool, serialization
- domain: mobile-development, cross-platform, developer-tools, tutorials
- platform: cpp, cross-platform
- tags: cross-platform-cpp, djinni, mobile-development, sample-project, gyp, android, ios, mobile

## Member repositories
- libmx3/mx3 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.540452+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:31:54.425833+00:00, confidence not recorded.
  - readme: https://github.com/libmx3/mx3 (fetched 2026-08-28T04:03:48.540452+00:00, sha cfed923b6905)
- Data as of 2026-08-30T08:39:29.467469+00:00.