Analysis updated 2026-05-18
Run an end-to-end research project, from topic exploration to a written report, in one traceable session.
Trace a generated figure or number back to the exact code and data that produced it.
Run experiments locally or on remote resources like SSH, Slurm, or Modal, with a reproducible record of each run.
Check on a research run from your phone or another device through a built-in authenticated gateway.
| ai4s-research/open-science | silvertakana/worldwideview | skevy/wobble | |
|---|---|---|---|
| Stars | 880 | 874 | 861 |
| Language | TypeScript | TypeScript | TypeScript |
| Last pushed | — | — | 2023-02-10 |
| Maintenance | — | — | Dormant |
| Setup difficulty | moderate | moderate | easy |
| Complexity | 3/5 | 4/5 | 2/5 |
| Audience | researcher | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires installing the desktop app and connecting an AI model provider, remote run features need SSH, Slurm, or Modal access.
Open Science Desktop is a desktop application, built for macOS, Windows, and Linux, that aims to run an entire research project inside one continuous, traceable session. It covers the whole loop from an initial idea to a finished paper: exploring the topic, surveying existing literature, forming a hypothesis, writing experiment code, analyzing results, producing figures, and writing up the findings. The project describes itself as an open-source alternative to Claude Science and similar AI-for-science tools, and it is built with Tauri, MCP, and agent skills. A bundled agent chains together specialist skills, one for exploring, one for surveying literature, one for experimenting, and one for writing, so each stage produces a real file you can inspect, such as a markdown document or a notebook, rather than just a chat message. Every figure, table, report, and run result links back to the exact code, inputs, environment, and model output that created it, so results can be traced and checked. The application is local-first: sessions, data, notebooks, and run records are stored in folders on your own machine, and nothing is sent elsewhere by default. It is also model-agnostic, meaning the interface talks to a bundled runtime called OpenCode, and you can choose which underlying AI model powers it. Runs can happen locally or on remote resources such as SSH, Slurm clusters, or Modal, and each is captured as a reproducible record rather than scrollback text in a terminal. A built-in gateway, off by default, lets you check on a running analysis from a browser on your phone or local network once you turn it on, without your API keys leaving your machine. The agent can also control your own Chrome browser, using your existing logins, to read live web pages, or use a separate private browser if you prefer. The project is licensed under MIT and reports ranking first on an external benchmark for autonomous research agents called ResearchClawBench.
Open Science Desktop is a local-first desktop app that runs an entire AI research workflow, from exploring a topic to a finished, traceable report.
Mainly TypeScript. The stack also includes TypeScript, Tauri, MCP.
Free to use for any purpose, including commercial use, as long as you keep the copyright notice, under the MIT license.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.