Skip to main content
Glama
Sign In
AudacityMCP

AudacityMCP

by xDarkzx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_dtmf

Generate custom DTMF tone sequences (digits, A-D, *, #) with adjustable amplitude, duty cycle, and duration for audio testing.

Instructions

Generate DTMF (telephone) tones.

Args: sequence: DTMF characters (0-9, A-D, *, #). Default: "0123456789" duty_cycle: Tone vs silence ratio percentage (0-100). Default: 55 amplitude: Amplitude (0-1). Default: 0.8 duration: Total duration in seconds. Default: 1.0

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": "generate_dtmf"
  }
}

Input Schema

NameRequiredDescriptionDefault
durationNo
sequenceNo0123456789
amplitudeNo
duty_cycleNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.5

TDQS

A3.8/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It explains parameter meanings and defaults but does not state side effects, whether the tone is inserted into a project, what the return value is, or whether the operation is non-destructive.

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 compact and front-loaded with the purpose, followed by a clean parameter list. Every line provides necessary information and there is no redundant or tangential content.

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?

For a simple generator, the purpose and full parameter documentation cover most selection and invocation needs. However, with no annotations and no output schema, a brief note on what the tool returns or whether it modifies the project would make it fully self-sufficient.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates by explaining all four parameters: valid DTMF characters for sequence, the meaning and range of duty_cycle, the amplitude range, and duration units. This adds substantial semantic value beyond the bare schema.

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 states 'Generate DTMF (telephone) tones' with a clear verb and specific resource. This distinguishes it from siblings like generate_tone, generate_noise, and generate_chirp by identifying the exact kind of signal produced.

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?

Usage is implied by the purpose: use this when DTMF telephone tones are needed. However, there is no explicit guidance about when to choose this over the many sibling generation tools, nor any mention of alternatives or exclusions.

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

Deploy Server

Other Tools