# henrypp/memreduct

Lightweight real-time memory management application to monitor and clean system memory on your computer.

Repository: https://github.com/henrypp/memreduct
Canonical: https://ross.abutalabs.com/products/memreduct
Language: C
License: GPL-3.0
License Family: copyleft
Topics: memory-management, memory-monitoring, memory, cleaner, windows, foss, monitor, mem-reduct
Last push: 2026-08-13T15:02:10+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 97, release rhythm 28, longevity 100
- inputs: {"age_days": 4279, "days_push": 20, "days_rel": 519, "gap_med": 52.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10287, forks 599 (observed 2026-08-28T04:10:41.497212+00:00)

## What it is
Mem Reduct is a lightweight Windows application that monitors system memory usage in real time and cleans system cache using undocumented Native API features. It is available as an installer or portable version and requires administrator rights.

## Use cases
- free up ram on windows
- monitor system memory usage in real time
- clean windows standby memory list
- reduce memory usage without restarting
- portable memory cleaner for windows

## When to choose
- you want a small, free, open-source memory cleaner for Windows 7-11
- you need real-time memory monitoring with automatic cleaning rules
- you prefer a portable tool that runs without installation

## When to avoid
- you are on Linux or macOS - it is Windows-only
- you expect guaranteed large memory savings - results vary ~10-50%
- you dislike tools that rely on undocumented system APIs

## Facets
- artifact type: application
- maturity: active
- function: monitoring, developer-tools
- domain: windows, developer-tools, performance
- platform: windows
- tags: memory-management, memory-cleaner, system-monitor, native-api, portable, foss, desktop

## Member repositories
- henrypp/memreduct (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:41.497212+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 2026-08-29T17:19:20.202102+00:00, confidence not recorded.
  - readme: https://github.com/henrypp/memreduct (fetched 2026-08-28T04:10:41.497212+00:00, sha 3ce60cc5e49a)
- Data as of 2026-08-30T08:39:29.467469+00:00.