frankensonos: Memory-safe Rust controller for your own Sonos speakers on your own LAN

by Dicklesworthstone · MCP Server · ★ 97

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

How to install frankensonos

git clone https://github.com/Dicklesworthstone/frankensonos

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

Security audit verdict: SAFE · quality 64/100

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.

asyncdlnahome-automationinteroperabilitymcpmodel-context-protocolrustsmart-homesocosonos

Quick Facts

Stars97
Forks6
LanguageRust
CategoryMCP Server
Quality Score64/100
Open Issues1
Last Updated2026-10-23
Created2026-10-06
Platformscli, mcp, rust
Est. Tokens~25k

About frankensonos

FrankenSonos Your Sonos, your way. A memory-safe Rust controller for the Sonos speakers you already own. It talks to them directly on your own network, so you can script them and let your own AI agents run them instead of the official app. -dea584) Status: under active development (pre-).

Compatible Skills

These tools work well together with frankensonos for enhanced workflows:

  • home-mind — semantic(0.29)+complementary+shared_fw(openai)+rare_topics+similar_pop (62%)

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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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