blatant-why — security grade SAFE, quality 74/100

Security audit verdict: SAFE · quality 74/100

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 001TMF · MCP Server · ★ 104

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

🔒 Is blatant-why safe to install? View the security audit →

About blatant-why

Open-source protein design agent for Claude Code Commercial platforms wrap open-source tools behind paywalls and call it a revolution. BY gives you direct access through Claude Code. No platform fees. Your tools, your compute, your designs. Source: trust us bro Quick Start (5 minutes) You don't need to be a developer. If you can open a terminal and paste commands, you can run BY.

ai-agentantibody-designboltzgenclaude-codecomputational-biologydrug-discoverymcp-serverprotein-engineering

Quick Facts

Stars104
Forks10
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score74.2945580834316/100
Open Issues2
Last Updated2026-05-21
Created2026-03-23
Platformsclaude-code, mcp, python
Est. Tokens~777k

Compatible Skills

These tools work well together with blatant-why for enhanced workflows:

  • SciAgent-Skills — semantic(0.26)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • claude-scientific-skills — semantic(0.23)+complementary+rare_topics+same_lang+shared_platform (57%)
  • Mck-ppt-design-skill — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)
  • AssemblyZero — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)

blatant-why alternative? Top 6 similar tools

Looking for a blatant-why alternative? If you're comparing blatant-why 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.

  • SciAgent-Skills by jaechang-hits · ⭐ 352

    197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, sin

  • awesome-bio-agent-skills by BioTender-max · ⭐ 140

    A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell an

  • RivalSearchMCP by damionrashford · ⭐ 131

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  • deterministic-agent-control-protocol by elliot35 · ⭐ 88

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  • mcp-google-map by cablate · ⭐ 457

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  • kindly-web-search-mcp-server by Shelpuk-AI-Technology-Consulting · ⭐ 388

    Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, C

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Frequently Asked Questions

What is blatant-why?

blatant-why is AI-powered biologics design campaign agent — multi-agent orchestration with BoltzGen, PXDesign, Protenix, and 200+ cloud tools. Antibodies, nanobodies, de novo binders, and beyond.. It is categorized as a MCP Server with 104 GitHub stars.

What programming language is blatant-why written in?

blatant-why is primarily written in Python. It covers topics such as ai-agent, antibody-design, boltzgen.

How do I install or use blatant-why?

You can find installation instructions and usage details in the blatant-why GitHub repository at github.com/001TMF/blatant-why. The project has 104 stars and 10 forks, indicating an active community.

What license does blatant-why use?

blatant-why is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to blatant-why?

The top alternatives to blatant-why on Agent Skills Hub include SciAgent-Skills, awesome-bio-agent-skills, RivalSearchMCP. 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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