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voice-analysis-mcp

voice-analysis-mcp

by Patience-dot-devl
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_quality

Assess audio recording quality by checking levels, clipping, noise floor, and SNR. Flags common issues to ensure reliable transcription and pitch analysis.

Instructions

Assess recording quality: levels, clipping, noise floor, estimated SNR.

Flags common problems (clipping, very low level, high background noise,
narrowband telephone audio). Run this before drawing conclusions from other
analyses — poor quality audio degrades transcription and pitch tracking.

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": {
      "path": "<path>"
    },
    "name": "analyze_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
end_timeNo
start_timeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. Lists what is flagged (clipping, low level, noise, narrowband) but lacks detail on behavioral aspects like output format, side effects, or thresholds. Adequate but incomplete.

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 efficient sentences with no fluff. The purpose is front-loaded in the first sentence, and the usage guidance is in the second. Every sentence earns its place.

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

Completeness3/5

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

Tool has 3 params, no output schema, and no annotations. Description covers purpose and usage context but omits parameter details and output behavior (e.g., what the flags look like). Not fully complete for a tool with this complexity.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not mention any of the three parameters (path, start_time, end_time). It adds no meaning beyond the schema, failing to compensate for the coverage gap.

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 assesses recording quality with specific aspects (levels, clipping, noise floor, SNR) and flags common problems. It distinctively focuses on quality assessment among sibling tools like transcribe or get_audio_info.

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

Usage Guidelines4/5

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

Explicitly instructs to run this before other analyses because poor quality degrades transcription and pitch tracking, providing clear context for when to use. Does not list explicit alternatives or when not to use, but the priority guidance is strong.

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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