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waveform-MCP

waveform-MCP

by jarmstrong158
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

audio_compare

Compare two audio files to identify loudness, peak, dynamic range, and spectrum differences. Returns dB values where positive indicates the first file is louder or brighter.

Instructions

Compare two audio files: returns LUFS / peak / DR diffs and a per-band spectrum diff in dB. Positive numbers mean file_a is louder/brighter than file_b in that dimension.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_a": "<file_a>",
      "file_b": "<file_b>"
    },
    "name": "audio_compare"
  }
}

Input Schema

NameRequiredDescriptionDefault
bandsNo
file_aYes
file_bYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

The description transparently explains the output semantics (diffs and sign meaning), and the compare operation is inherently non-destructive. It does not explicitly state side-effect-free behavior, but the nature of the operation makes that clear.

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?

The description is concise and well-structured, using a single sentence to convey purpose, metrics, and sign convention without unnecessary detail.

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?

The description covers purpose, output metrics, sign convention, and the core operation. It omits parameter-level detail (especially bands) and does not specify output format, but for a simple comparison tool, it is sufficiently complete for an agent to invoke it correctly.

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?

file_a and file_b are inferable as the two audio files, but the 'bands' parameter is not explained (only defaulted to 10). The schema provides types and required status but no descriptive detail, so parameter meanings are incomplete.

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

Purpose5/5

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

The description clearly states the tool's purpose: compare two audio files, and it specifies the exact metrics returned (LUFS, peak, DR, per-band spectrum diff) and the sign convention (positive means file_a louder/brighter). This distinguishes it from single-file analysis tools.

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

Usage Guidelines3/5

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

The description implies usage when comparing two audio files, but it does not explicitly name alternative tools or state when to choose this over single-file analyzers like audio_loudness_lufs or audio_spectrum. Guidance is implicit rather than explicit.

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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