open-science — security grade SAFE, quality 60/100

Security audit verdict: SAFE · quality 60/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by aipoch · MCP Server · ★ 4.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is open-science safe to install? View the security audit →

About open-science

Open Science An open-source, model-agnostic AI workbench for scientific discovery. Open Science is a local desktop application for researchers. Create a project, describe a task in plain languag

ai-for-scienceai-researchai-workbenchbioinformaticsclaude-science-alternativedesktop-appelectronlinuxlocal-firstmacos

Quick Facts

Stars4,180
Forks270
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score60.2789869653536/100
Open Issues33
Last Updated2026-09-14
Created2026-07-03
Platformsclaude-code, mcp, node
Est. Tokens~21k

Compatible Skills

These tools work well together with open-science for enhanced workflows:

  • open-science — semantic(0.63)+rare_topics+same_lang+similar_pop+shared_platform (72%)
  • ai4s-skills — semantic(0.39)+complementary+rare_topics+similar_pop (64%)
  • claude-prism — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • VersperClaw — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)
  • pawwork — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)

open-science alternative? Top 6 similar tools

Looking for a open-science alternative? If you're comparing open-science with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • open-science by ai4s-research · ⭐ 1.6k

    Open Science Desktop — local-first, model-agnostic AI research workbench for macOS, Windows & Linux. Open-sour

  • wisp-science by xuzhougeng · ⭐ 1.1k

    Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformat

  • XHS-Downloader by JoeanAmier · ⭐ 12.7k

    小红书(XiaoHongShu、RedNote)链接提取/作品采集工具

  • nginx-ui by 0xJacky · ⭐ 11.5k

    Yet another WebUI for Nginx

  • Kiln by Kiln-AI · ⭐ 5.1k

    Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation,

  • amical by amicalhq · ⭐ 1.5k

    🎙️ AI Dictation App - Open Source and Local-first ⚡ Type 3x faster, no keyboard needed. 🆓 Powered by open so

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Frequently Asked Questions

What is open-science?

open-science is AIPOCH Open-Science is an open-source, local-first, model-agnostic AI research workbench for macOS, Windows, and Linux, with scientific agents, Python/R notebooks, data connectors, and reproducible pr. It is categorized as a MCP Server with 4.2k GitHub stars.

What programming language is open-science written in?

open-science is primarily written in TypeScript. It covers topics such as ai-for-science, ai-research, ai-workbench.

How do I install or use open-science?

You can find installation instructions and usage details in the open-science GitHub repository at github.com/aipoch/open-science. The project has 4.2k stars and 270 forks, indicating an active community.

What license does open-science use?

open-science is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to open-science?

The top alternatives to open-science on Agent Skills Hub include open-science, wisp-science, XHS-Downloader. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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