Resonant: Free, local AI music studio for Windows—generate songs, play instruments, arrange, mix, export WAV

by calesthio · MCP Server · ★ 138

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

Security audit verdict: SAFE · quality 52/100

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.

ace-stepai-musicdigital-audio-workstationelectrongenerative-musicmcpmodel-context-protocolmusic-productionopen-sourcetypescript

Quick Facts

Stars138
Forks16
LanguageTypeScript
CategoryMCP Server
LicenseAGPL-3.0
Quality Score52/100
Open Issues1
Last Updated2026-08-07
Created2026-08-02
Platformsclaude-code, codex, mcp, node
Est. Tokens~13k

About Resonant

Make complete songs locally. Write, generate, perform, personalize vocals, arrange, mix, and export—all on your computer. Resonant is a free, open-source AI music studio and production workstation for Windows. Think of it as a local alternative to cloud music generators such as Suno, with a real clip launcher, arrangement timeline, instrument library, mixer, and an MCP server for AI assistants.

Compatible Skills

These tools work well together with Resonant for enhanced workflows:

  • codevator — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)

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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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