ai4s-research/open-science: A Local-First AI Research Workbench for Scientists

🎉 Recognition: Open Science Desktop ranks #1 by scored-task average on ResearchClawBench, an end-to-end benchmark for autonomous scientific research agents (Pass@1 leaderboard, July 9, 2026).

What it does

Runs the whole research loop — from a broad direction to a finished paper: exploration, literature survey, hypothesis, experiment code, analysis, figures, and write-up, in one continuous, auditable session.

• Autonomous research agents — the bundled ai4s-agent chains specialist skills end to end (explore → survey → experiment → write), and each stage drops a real, inspectable artifact into your workspace, not just a chat reply.
• Everything traces back — figures, tables, reports, notebooks, and run outputs link to the exact code, inputs, environment, model output, and conversation that produced them.
• Local-first and yours — sessions, data, provenance, notebooks, and run records live in local folders on your machine. Nothing leaves by default.
• Model-agnostic runtime — the UI talks through packages/sdk to a bundled, pinned OpenCode sidecar. Bring your own model; providers, skills, and MCP servers stay pluggable.
• Reproducible by construction — local, SSH/Slurm, Modal, and notebook-batch runs are captured as reproducible run records, not loose terminal scrollback.
• Extensible — agent skills, MCP servers and one-click science connectors, / commands, ! shell mode, and a model-agnostic SDK.

See it in action

One prompt -> a complete, traceable analysis. Simulate data, fit a model, save a publication-grade figure, and write a report where every number traces to the code.

Every artifact traces back to its code, inputs, and conversation.

Literature -> verifiable report. Search papers, draft a manuscript rendered as a PDF, and audit citations, unsourced numbers, and figure/code consistency.

Current capabilities

The research loop, as skills. One meta-skill runs the full pipeline; each stage is a self-contained skill that produces a real, gradeable artifact — runnable on any model OpenCode supports:

These ship in the ai4s-skills pack alongside first-party review skills and the office/document skills below.

Platform

Skills and connectors

Bundled skills are fetched for builds and releases instead of being committed into git history:

• ai4s-skills pack from ai4s-research/ai4s-skills.
• Office/document skills from the Apache-2.0 anthropics/skills repository: docx, pdf, pptx, and xlsx.
• First-party core skills in runtime/skills/core/: traceability-review, stats-integrity, domain-check, large-file, publication-figures, remote-compute, and modal-run.

One-click science MCP connectors currently include:

• Literature search: arXiv, PubMed, Crossref, Semantic Scholar, bioRxiv/medRxiv.
• Biomedical databases: PubMed, ClinicalTrials.gov, MyVariant/ClinVar.
• Materials Project.
• FRED economic data.
• Space weather.
• Open-Meteo weather and climate.
• USGS water data.

You can also add any local or remote MCP server from Settings. See docs/CONNECT_YOUR_TOOLS.md.

For a neutral positioning note, see Open Science Desktop vs OpenScience.

Install

Download the latest installer from the Releases page.

• macOS: .dmg / .app, Apple Silicon and Intel, macOS 13 Ventura or later.
• Windows: NSIS .exe and .msi, Windows 10/11 x64.
• Linux: .deb and .rpm on x86_64 Linux.

Builds are not code-signed or notarized yet.

macOS: if Gatekeeper says the app is damaged or from an unidentified developer, install it into Applications and run:

xattr -cr "/Applications/Open Science.app"

Windows: if SmartScreen appears, choose More info -> Run anyway.

Linux:

sudo apt install ./OpenScience_*.deb
# or
sudo rpm -i OpenScience_*.rpm

Build from source

Prerequisites:

• Node.js >= 20
• pnpm 9
• Rust toolchain
• macOS, Windows, or Linux system dependencies required by Tauri

git clone https://github.com/ai4s-research/open-science
cd open-science
pnpm install

# Fetch pinned sidecars and bundled skills. These are git-ignored.
bash scripts/dev/fetch-opencode.sh
bash scripts/dev/fetch-uv.sh
bash scripts/dev/fetch-skills.sh

# Run in development or build installers.
pnpm --filter @ai4s/desktop tauri dev
pnpm --filter @ai4s/desktop tauri build

Useful checks:

pnpm test
pnpm typecheck
pnpm lint

Safety and privacy

• Workspace files, raw data, session history, provenance, notebooks, and run records stay local by default.
• Command execution, file deletion, dependency installation, and remote connections are human-approved flows in the desktop app.
• Provider credentials are written to app-private runtime config, not to the workspace, provenance, git, exports, or global OpenCode config.
• Settings includes a plain-language data-flow view explaining what can be sent to the selected model provider.

Repository layout

Status

The project is a working desktop MVP in active development. The most reliable current implementation log is PROGRESS.md. Product and architecture notes live in docs/PRD.md and docs/TECHNICAL_DESIGN.md, but those documents include target design as well as historical status notes.

Near-term work is focused on signed/notarized releases, broader Windows/Linux verification, auto-update, richer connector hardening, and continued reproducibility review.

Citation

If you use Open Science Desktop in your research, please cite it:

@software{open_science_desktop,
  author  = {{The Open Science Desktop Contributors}},
  title   = {Open Science Desktop: a local-first, model-agnostic AI research workbench},
  year    = {2026},
  version = {0.2.0},
  doi     = {10.5281/zenodo.21351226},
  url     = {https://github.com/ai4s-research/open-science},
  license = {MIT}
}

GitHub's "Cite this repository" button (top of the repo page, generated from CITATION.cff) provides the same reference in APA and BibTeX.