Show HN: A possible open-source desktop alternative to OpenAI Codex

An open-source desktop alternative to OpenAI Codex, called Open Science Desktop, has been released for macOS, Windows, and Linux. The tool provides a local-first, model-agnostic AI research workbench that connects agents, notebooks, files, and reports into an auditable workflow, and it ranks first on the ResearchClawBench benchmark for autonomous scientific research agents.

Local-first, model-agnostic AI research workbench for macOS, Windows & Linux. Formerly Open Science. An open-source desktop alternative to Claude Science and similar AI-for-science workbenches — built with Tauri, MCP, agent skills, and reproducible artifacts. It connects agents, notebooks, files, figures, reports, runs, and review into one auditable desktop workflow. 🎉 Recognition: Open Science Desktop ranks 1 by scored-task average on ResearchClawBench https://internscience.github.io/ResearchClawBench-Home/ , an end-to-end benchmark for autonomous scientific research agents Pass@1 leaderboard, July 9, 2026 . ✨ What it does what-it-does 🎬 See it in action see-it-in-action 🧪 Current capabilities current-capabilities 🔌 Skills and connectors skills-and-connectors 📦 Install install 🚀 Build from source build-from-source 🔒 Safety and privacy safety-and-privacy 🗂️ Repository layout repository-layout 📌 Status status 🤝 Contributing contributing ⚖️ License license 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. 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. 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: | Skill | Role | Primary output | |---|---|---| ai4s-agent | Runs the four skills below, in order | The full research package | research-explorer | Turn a broad direction into concrete topics | research exploration.md , topic matrix.md , literature pre survey.md | literature-survey | Write a literature survey | 6–20 pp PDF, 60+ real citations, LaTeX source, taxonomy figures | experiment-suite | Build an experiment package | Design doc, runnable code, results.json with provenance, figures, report | paper-writer | Write a research paper | 8–14 pp PDF, 200+ citations, 4–8 figures, tables | mindmap-render | Render a mindmap | Image generated from a topic matrix.md | integrity-auditor | Audit a paper's integrity | Image / numerical / logical findings, 4-level evidence grading, audit report.md | These ship in the ai4s-skills pack alongside first-party review skills and the office/document skills below. | Area | Current state | |---|---| | Desktop shell | Tauri 2 + React + TypeScript + Vite, with macOS, Windows, and Linux desktop builds. | | Runtime | Bundled OpenCode sidecar, auto-started by the app, isolated from the user's own OpenCode config/data. | | Sessions | Multi-session chat/history, dated workspace folders, global history across workspaces, / commands, and shell mode. | | Files | Global and per-session file browsing, context menu actions, external open/reveal, copy path, and local preview server. | | Notebooks | Real .ipynb files, Python and R notebook creation, local kernel execution, managed Jupyter environment via bundled uv , and an Open JupyterLab action. | | Runs | Append-only run logs, global SQLite run index, search/facets/pagination, local/remote surfaces, output links, logs, and reproduce prompts. | | Provenance | .openscience/provenance.jsonl tracks file versions and links produced artifacts back to the run or edit that created them. | | Review | Traceability, statistics-integrity, domain-check, large-file, publication-figure, remote-compute, and Modal run skills are bundled as first-party skills. | | Viewers | PDF, image, video, HTML, Markdown, code, CSV/TSV tables with charts, DOCX, XLSX, PPTX, molecules, 3D meshes, genome tracks, FITS, DOS/DOSCAR, EIGENVAL bands, qcode, anomaly maps, and phase files. | | Models | OpenCode provider catalog, OAuth/API-key provider flows, custom OpenAI-compatible endpoints, and local/provider-specific options supported by OpenCode. | | Interface languages | English, Simplified Chinese, Japanese, Spanish, German, French, and Korean. Portuguese Brazil and Arabic are registered but not selectable yet. | 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 /ai4s-research/open-science/blob/master/docs/CONNECT YOUR TOOLS.md . For a neutral positioning note, see Open Science Desktop vs OpenScience /ai4s-research/open-science/blob/master/docs/open-science-desktop-vs-openscience.md . Download the latest installer from the Releases page https://github.com/ai4s-research/open-science/releases/latest . 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 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 - 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. | Path | Purpose | |---|---| apps/desktop/ | Tauri + React desktop app. | packages/sdk/ | OpenCodeClient ; keeps the UI from calling OpenCode directly. | packages/shared/ | Shared domain types and chart palette. | packages/ui/ | Shared UI package. | runtime/skills/core/ | First-party scientific skills. | runtime/skills/external/ | Build-fetched external skills. | runtime/harness/ | Runtime harness knowledge and operator context. | runtime/mcp/ | MCP runtime notes/configuration. | examples/ | Built-in example workspaces. | scripts/dev/ | Sidecar, uv , skill fetchers, and focused regression probes. | docs/ | Product, technical, operator, connector, and research notes. | The project is a working desktop MVP in active development. The most reliable current implementation log is PROGRESS.md /ai4s-research/open-science/blob/master/PROGRESS.md . Product and architecture notes live in and /ai4s-research/open-science/blob/master/docs/PRD.md docs/PRD.md , but those documents include target design as well as historical status notes. /ai4s-research/open-science/blob/master/docs/TECHNICAL DESIGN.md docs/TECHNICAL DESIGN.md Near-term work is focused on signed/notarized releases, broader Windows/Linux verification, auto-update, richer connector hardening, and continued reproducibility review. Issues and PRs are welcome. Keep changes minimal and verifiable, follow AGENTS.md /ai4s-research/open-science/blob/master/AGENTS.md , and run the checks before opening a PR. For discussion, join the Open Science Discord https://discord.gg/fWNMDKcd5P or the linux.do https://linux.do community. MIT /ai4s-research/open-science/blob/master/LICENSE . Bundled third-party skills and connectors keep their own licenses. Open Science Desktop is beta research tooling. Treat outputs as drafts: verify numbers, citations, code, and conclusions before publication or decision-making.