jarvis-assistant-vocal: Assistant vocal local en francais : Claude ou Ollama, domotique Hue, OBS, agenda, navigateur, appels Twilio

by sosoj92 · MCP Server · ★ 486

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

Security audit verdict: SAFE · quality 59/100

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.

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.

anthropic-claudebrowser-automationhome-automationjarvislocal-aimcpmcp-serverobsollamaphilips-hue

Quick Facts

Stars486
Forks138
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score59/100
Open Issues10
Last Updated2026-10-20
Created2026-08-07
Platformsbrowser, claude-code, mcp, python
Est. Tokens~15k

About jarvis-assistant-vocal

🤖 Jarvis — assistant vocal local English version Un assistant vocal en français qui tourne sur ta machine. Dis « Hey Jarvis », parle naturellement : il raisonne avec un LLM, utilise une boîte à outils extensible (domotique, PC, web, téléphone…) et te répond à voix haute. Deux modes au choix, en une ligne de config : cloud (Claude + ElevenLabs) ou 100 % local hors ligne (Ollama + Piper).

Compatible Skills

These tools work well together with jarvis-assistant-vocal for enhanced workflows:

  • home-generative-agent — semantic(0.31)+complementary+shared_fw(ollama)+rare_topics+same_lang+similar_pop+shared_platform (73%)
  • clawos — semantic(0.28)+complementary+shared_fw(ollama)+rare_topics+same_lang+similar_pop+shared_platform (72%)
  • writher — semantic(0.32)+complementary+shared_fw(ollama)+same_lang+similar_pop+shared_platform (69%)

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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:

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