VerifiedPlugin
Research
Plugin
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.
Plugin Signal82/100Strong
maintained100
capable68
documented75
adopted80
Install
$ npx -y skills add aipoch/open-science --agent claude-code
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Maintenance
TypeScript
Language
Apache-2.0
License
22m ago
Last commit
3mo ago
Created
13h ago
Added
Repo: aipoch/open-science
What's inside
Skill(25 skills)
/alphafold2Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate/boltzStructure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get/borzoiPredict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding
README
AIPOCH Open-Science is an AI research workbench for scientists and researchers, developed by AIPOCH with an open-source, local-first, model-agnostic approach. 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.
AIPOCH 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.
Completed research sessions can also be exported as portable .science packages for review, handoff, and archiving, with selected conversation branches, file versions, Notebook records, and verification evidence.
💡 AIPOCH Open-Science v0.35.1 released (last updated October 2026). AIPOCH Open-Science v0.35.1 brings GWAS summary statistics discovery, InterProScan sequence submission, and IEDB receptor evidence searches to the connector catalog, refreshes the new-conversation start experience with a common-actions session menu, and adds the Requesty provider. Fixes preserve composer context across session binding, keep imported sessions read-only, protect replay follow-ups, and harden PDF, notebook, and workspace reliability. See the latest release notes for full details.
Table of Contents
- Quick Start
- Product Tour
- AIPOCH Open-Science
.scienceResearch Packages - Benchmark Performance
- Core Capabilities
- Model Providers
- Data, Permissions, and Trust
- Development & Packaging
- Frequently Asked Questions
- Get Involved
- License
- Star History
🚀 Quick Start
1. Download the app
Open the official download page and choose the installer for your computer:
| Your computer | Choose |
|---|---|
| macOS 12+ — Apple Silicon (M1 or newer) | The macOS DMG for Apple Silicon / ARM64 |
| macOS 12+ — Intel | The macOS DMG for Intel / x64 |
| Windows x64 | The Windows x64 installer (code-signed) |
| Linux x64 | The Linux x64 AppImage or Debian package |
Download from the official download page; see download verification if needed.
On macOS, you can also install with Homebrew:
brew install --cask open-science
Windows reinstalls preserve research data. For a full cleanup, see the data reset tool, which permanently deletes local data after confirmation.
2. Complete first-time setup
Follow the setup wizard: Environment → Data location → Agent runtime → Model provider → Notebook runtime.
Complete the required environment and agent-runtime checks and test your model connection. Python/R Notebook setup is optional; Notebook and data-location settings can be changed later.
3. Start a research project
- Click New project, open a session, and describe your research goal, inputs, and expected outputs.
- Attach files, select a model and approval mode, then send the task. Use
@to reference project files or/to choose a skill. - Review tool activity and any approval requests, preview the results, and check their available evidence in Provenance.
Screenshots in this README illustrate the workflow. Labels, catalogs, and other interface details may differ from the version you install.
Product Tour
From a research request to a traceable result
Consider a representative bioinformatics task: reproduce a published differential-expression analysis, compare the regenerated results with the paper, and deliver the report, tables, and figures needed for review. The screenshots below are representative views from documented AIPOCH Open-Science workflows; they illustrate each stage rather than one continuous session.
1. Define the research task and evidence
Describe the research question, source paper and datasets, required methods or thresholds, expected outputs, and acceptance criteria. Upload supporting files or reference an existing project artifact with @, so the agent starts from explicit inputs instead of hidden context.
2. Execute with inspectable scientific tools
The agent can combine scientific skills, permissioned research connectors, searches, file operations, and Python or R code in the shared Notebook. Generated figures can be reviewed beside the research summary, while the artifact record exposes captured producer code and execution evidence for inspection.
3. Review reports, tables, and figures in place
The final response summarizes what reproduced, what differed, and which limitations matter. Generated Markdown reports, CSV tables, images, and other research artifacts remain attached to the session and are collected in the project file library, where they can be previewed beside the conversation and reused in follow-up work.
4. Trace every artifact back to its evidence
Each generated artifact is stored as an immutable, checksummed version. Its Provenance view can expose the producing code and execution history, referenced inputs, observed environment inventory, producing conversation branch, and version-scoped Reviewer findings. Evidence that could not be verified is marked unavailable rather than inferred.
AIPOCH Open-Science .science Research Packages
Export a completed research session as a portable .science package for review, handoff, and archiving. Choose the conversation branches, file versions, Notebook records, and verification evidence to include, then import the package into another project or computer.
Export → transfer → inspect
- Export a completed session and choose the contents to include.
- Move the
.sciencefile to a collaborator or another computer. - Import it into a project. The right-hand Research replay shows the recorded process; the left-hand conversation lets you ask about it and follow fixed step references.
Imported records remain read-only. Watching a replay does not execute code, call a model, or restore credentials. Your first question creates an associated writable discussion; use Create a copy to continue research to run follow-up experiments. Re-executing a result still requires a complete recipe, required inputs, and an available runtime.
Benchmark Performance
🏆 #1 on BiomniBench-DA Public 50
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View @aipoch’s profileFAQ
open-science is a Claude Code plugin with 25 hand-picked skills for research work, indexed on Flowy. Install it with the command on its page. It includes alphafold2, boltz, borzoi. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is 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.
- How do I install open-science?
- Run these in Claude Code: npx -y skills add aipoch/open-science --agent claude-code. Then prompt normally.
- Does open-science auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is open-science free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.
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