Automate repetitive in-game chores like fishing, selling fish and restocking bait.
Automatically collect daily rewards and seasonal pass items.
Skip story dialogue and use an audio based helper to dodge and counter in combat.
| therunicdev/maante | littlefrogyq/ue4ss-subnautica-2 | sveltejs/cli | |
|---|---|---|---|
| Stars | 484 | 483 | 483 |
| Language | — | C++ | TypeScript |
| Last pushed | — | — | 2026-07-03 |
| Maintenance | — | — | Active |
| Setup difficulty | moderate | easy | easy |
| Complexity | 3/5 | 2/5 | 2/5 |
| Audience | general | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires the game running in windowed mode at a fixed 1280x720 resolution, using it risks account penalties under the game's fair play rules.
MaaNTE is a Windows automation toolkit for the game Neverness to Everness, built on top of an existing project called MaaFramework. It uses image recognition to watch the screen and simulate mouse and keyboard actions, so it can handle repetitive in-game chores without a person doing them by hand. The README lists specific features rather than vague promises: automated fishing that includes selling fish and restocking bait, running a coffee shop by automatically dismissing customers, collecting daily rewards such as activity points and season pass items, smart teleportation, skipping story dialogue automatically, and an audio based combat helper that can dodge and counter attacks. Some features, described as "Super Sonic" and "Lost Star," are tuned for a rhythm or performance related part of the game. The developers describe the project as only simulating clicks and screen reading, not modifying game files or memory, and say it is meant to remove repetitive tasks rather than give players an unfair edge. Even so, they include a clear warning that the game's own fair play rules prohibit third party tools that provide an advantage, and that using automated farming or similar features can lead to account penalties, including permanent bans. The README also warns that unofficial copies of this software circulating elsewhere may contain malware, and tells users to only download from the official GitHub repository. Regular users install a prebuilt release from the Releases page, while developers can fork the repository and set up a Python 3.11 or newer environment, ideally with a supporting VS Code extension. The project targets a fixed game window resolution of 1280x720 and needs decent performance for its fishing feature. It is licensed under the GNU Affero General Public License version 3.
A Windows automation tool for the game Neverness to Everness that uses image and audio recognition to handle repetitive tasks like fishing and daily rewards.
You can use and modify this freely, but if you run a modified version as a network service, you must share your source code too.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.