aipoch/open-science
The open-source AI research workbench for scientific research and agent workflows. Local-first, model-agnostic desktop app with extensible skills, MCP tools and connectors, Python/R execution and traceable artifacts for reproducible research on macOS, Windows and Linux.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest today, with 26 contributors on GitHub.
The biggest single-day gain in the last year, +320 stars on Sep 7, coincided with release v0.26.0.
Use Cases & Benefits
- Provides a local-first, model-agnostic AI research workbench for reproducible scientific research with agent workflows, Python/R execution, and traceable artifacts on desktop platforms.
- Enables integrated, inspectable, and durable research by combining project management, multi-model AI agents, scientific data connectors, and human-in-the-loop control in one extensible workspace.
- Use for managing and executing reproducible computational research projects across disciplines like life sciences, chemistry, and physics with traceable provenance of results.
- Use for developing and iterating on scientific AI agent workflows that read data, run code, query databases, and generate reports with versioned artifacts.
- Use for integrating and extending scientific skills and data connectors to automate literature review, data analysis, simulation, and visualization within a single desktop app.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Open-source, local-first, model-agnostic AI research workbench for reproducible science.
Open Science is an open-source, local-first, model-agnostic AI research workbench developed by AIPOCH for scientists and researchers. It enables reproducible, inspectable research with scientific AI agents, Python and R execution, scientific data connectors, and cross-platform support for macOS, Windows, and Linux. Create a project, describe your research goal in plain language, and let the agents read files, search the web, run code, query scientific data sources, and produce reports, tables, and figures with traceable provenance—all in one workspace.
Open Science supports computational and data-intensive research across disciplines, including machine learning, statistics, life sciences, chemistry, materials science, physics and environmental science. It supports the research process from literature review and hypothesis development to code execution, data analysis, simulation, visualization, and the production of traceable research outputs.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+1,628 stars over 53 days across 15 snapshot days; best day +320 on Sep 7.
Forks
541+304
Open issues
44-2
Compared with peers in iOS
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| vercel-labs/agent-desktop | 17.0K | +13.3K | 33 | today |
| nightly-labs/openbot | 5.8K | +2.0K | 45 | today |
| rustdesk/rustdesk | 128.3K | +839 | 65 | 4 days ago |
| crmne/zapfast | 3.1K | +839 | 60 | 2 days ago |
| makecindy/cindy | 9.3K | +771 | 45 | today |
| aipoch/open-science | 5.4K | — | 40 | today |
| Category median | 9.3K | +839 | 45 | — |
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