k-dense-byok: An AI co-scientist running on your desktop. Claude Science but better

by K-Dense-AI · MCP Server · ★ 1.4k

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

How to install k-dense-byok

git clone https://github.com/K-Dense-AI/k-dense-byok.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-aiai-agentai-assistantbioinformaticsbyokdrug-discoverygoogle-adklitellmlocal-firstmcp

Quick Facts

Stars1,359
Forks174
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score66/100
Open Issues11
Last Updated2026-10-16
Created2026-03-19
Platformsclaude-code, mcp, node, python
Est. Tokens~16k

About k-dense-byok

K-Dense BYOK Your own AI research assistant, running on your computer, powered by your API keys. K-Dense BYOK (Bring Your Own Keys) is a free, open-source app that gives you an AI research assistant called Kady.

Compatible Skills

These tools work well together with k-dense-byok for enhanced workflows:

  • PhD-Zero — semantic(0.44)+complementary+similar_pop+shared_platform (50%)
  • claude-prism — semantic(0.36)+complementary+same_lang+shared_platform (48%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

View on GitHub → Browse MCP Server tools