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@audiolabtools/mcp-server

by Audio-Launch
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JavaScript
Hybrid

Analyze loudness (MixLab)

analyze_loudness

Measure integrated LUFS, true-peak, loudness range, crest factor, and stereo correlation from audio files via URL or local path to ensure broadcast loudness compliance.

Instructions

Loudness and dynamics for a track: integrated LUFS (EBU R128 / BS.1770-4), true-peak (dBTP), loudness range (LRA), crest factor, stereo correlation, mono compatibility, and tonal balance. Audio source: a public https URL, or a local file path (path).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "analyze_loudness"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlNoPublic https URL to the audio file. Provide exactly one of url or path.
pathNoPath to a LOCAL audio file on this machine, analysed without hosting it publicly (files up to 4 MB are sent inline; larger ones up to 150 MB upload over a signed URL). Provide exactly one of url or path.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It discloses essentially nothing beyond the metric list — no read-only/side-effect profile, no latency or cost characteristics, no auth requirements, and no indication of how large files or failures are handled (the 4 MB inline / 150 MB signed-URL detail lives in the schema, not the description).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the substantive metric list and closing with the input-source clause. Every phrase carries information (specific standards named, concrete metrics enumerated) and there is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema present, the description usefully compensates by enumerating the returned measurements, and the input contract is fully covered by the schema. It is slightly incomplete in that it gives no behavioral context (safe read? latency? cost?) for an analysis operation with zero annotation coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (url and path) are already fully documented in the schema, including the 'exactly one of' constraint and the size thresholds. The description only restates the two source options without adding format or constraint detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (loudness/dynamics analysis of a track) and enumerates the exact metrics produced — integrated LUFS, true-peak, LRA, crest factor, stereo correlation, mono compatibility, tonal balance — which clearly separates it from siblings like get_spectrum or analyze_voice. It does not explicitly name the nearest sibling compare_loudness, so it falls short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says what it analyzes but never states when to choose this tool over alternatives such as compare_loudness or get_spectrum. There is no when-to-use, when-not-to-use, or prerequisite guidance; the only routing hint is the input source format, which is parameter information rather than usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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