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 ywatanabe1989 · MCP Server · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is scitex-python safe to install? View the security audit →
SciTeX (scitex) Python Library for Science. For AI and Human Researchers Docs · Quick Start · API · pip install scitex[all] This repository provides , the orchestration layer of the SciTeX ecosystem — solving key problems in scientific research: Problem and Solution Proble
| Stars | 85 |
| Forks | 22 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 68.5805888235083/100 |
| Open Issues | 63 |
| Last Updated | 2026-06-20 |
| Created | 2025-06-13 |
| Platforms | mcp, python |
| Est. Tokens | ~22k |
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scitex-python is Umbrella package for SciTeX — reproducible science from raw data to manuscript. It is categorized as a MCP Server with 85 GitHub stars.
scitex-python is primarily written in Python. It covers topics such as academic-writing, ai-research, automation.
You can find installation instructions and usage details in the scitex-python GitHub repository at github.com/ywatanabe1989/scitex-python. The project has 85 stars and 22 forks, indicating an active community.
scitex-python is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to scitex-python on Agent Skills Hub include scitex-python, mcp-gateway, mcp-trader. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: