FRENES

Image, video and audio · MCP server

Audio analyzer rs: MCP server, setup and security

Audio analyzer rs is an open-source MCP server published on GitHub that lets an AI agent analyze audio spectrum, harmony, rhythm, stereo properties and structural features. Its repository has 70 stars and its last commit is from March 15, 2026 and it is licensed under MIT.

Score
43/100
Adoption (stars) 18/40
Maintenance 10/30
Framework (licence, registry, official) 15/30
Last commit 7 months ago

What Audio analyzer rs does

According to its repository: “Gives LLMs ears. Spectral, harmonic, rhythm, stereo, and structural audio analysis.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Audio analyzer rs is listed under Image, video and audio, a category of 67 servers in the directory, where it ranks #33 by stars.

Installing and connecting Audio analyzer rs

Distribution modes declared in the official MCP registry:

  • MCPB bundle (one-click install in Claude Desktop)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Rust.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Audio analyzer rs. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on March 8, 2026, the JuzzyDee/audio-analyzer-rs repository has 70 stars and 12 forks, with 0 open issues. It has more stars than 59% of the servers in the directory. Last change 7 months ago. Version published in the registry: 1.0.0 (March 13, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

ScreenpipeScreenpipe : 22.1K22.1KFunASRFunASR : 20.8K20.8KRemove AI WatermarksRemove AI Watermarks : 6.1K6.1KOpenScreenOpenScreen : 4.9K4.9KOpenPostOpenPost : 755755FableCutFableCut : 746746Anki MCP ServerAnki MCP Server : 531531MCP youtube transcriptMCP youtube transcript : 492492Audio analyzer rsAudio analyzer rs : 7070
GitHub stars of the most followed servers in the category (log scale); Audio analyzer rs in orange. Checked October 25, 2026.

Verdict

Audio analyzer rs is still a modest project: read its code and compare it with the alternatives before using it.

Strengths

  • Listed in the official MCP registry
  • Permissive licence (MIT)

Limitations

  • No commit for 7 months

Frequently asked questions

How do I install Audio analyzer rs?

Audio analyzer rs is distributed as MCPB bundle (one-click install in Claude Desktop). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of JuzzyDee/audio-analyzer-rs.

Is Audio analyzer rs free?

The code is published under the MIT licence and can be used free of charge.

Is Audio analyzer rs safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by JuzzyDee on GitHub. Check who maintains it before giving it access.

What are the alternatives to Audio analyzer rs?

In the same category: OpenScreen, Remove AI Watermarks, FunASR, and Oh My Cassette. OpenScreen and Remove AI Watermarks score higher on our grid.

Related articles

Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score