# Audio Analysis MCP Server

> Use this tool when you need to analyze audio files without direct playback, and want to compare iterations or detect patterns through numerical fingerprints, pitch tracking, and visual spectrograms. It solves problems such as audio pattern recognition, iteration comparison, and token-efficient analysis, and takes in audio files as input, outputting numerical and visual representations. Ideal for use cases where audio analysis is required without the need for playback, such as audio classification, tagging, or searching.

Canonical page: https://skillsregistry.net/skills/zachswift615-audio-analysis-mcp  
JSON: https://api.skillsregistry.net/v1/skills/zachswift615-audio-analysis-mcp

## Description

Enables AI models to analyze audio files through numerical fingerprints, pitch tracking, and visual spectrograms without requiring direct audio playback. It provides tools for comparing audio iterations and detecting patterns using token-efficient analysis operations.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-04-22

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fw327nxgj9)
- **Repository:** <https://github.com/zachswift615/audio-analysis-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "zachswift615-audio-analysis-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zachswift615-audio-analysis-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zachswift615-audio-analysis-mcp/pull`

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