Agent Toolbox

Transcribe Audio

transcribe_audio

Read-only

Speech to text with Whisper large v3 turbo: transcribe audio (mp3, wav, m4a, ogg, webm; up to 20 MB, about 20 minutes) from a URL or base64, or translate the speech into English. Returns the text, language, duration and timed segments. Costs USD 0.01 per call, paid with x402 (USDC on Base); calls that fail are not charged.

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": "transcribe_audio"
  }
}

Input Schema

Name	Required	Description
`task`	No	translate = into English
`language`	No	Language code such as en or hi (detected when left out)
`audio_url`	No	A public http(s) URL
`audio_base64`	No	The audio file, base64-encoded

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 24, 2026

TDQS

A4.5/5.0

Behavior5/5

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

It adds substantial behavior beyond the annotations: cost per call, payment rail, non-charging on failure, file-size and duration limits, and the return fields. These are exactly the operational details an agent needs before invocation, and nothing contradicts the read-only, open-world annotations.

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 text is front-loaded with the core operation and then packs limits, source options, output fields, payment cost, and failure policy into a dense but waste-free description. Every clause earns its place.

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

Completeness5/5

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

With no output schema, the description correctly supplies the return shape (text, language, duration, timed segments) and enough input, cost, and failure context for an agent to call the tool safely and correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description still adds useful parameter-facing detail not present in the schema, especially allowed audio formats and the 20 MB / ~20 minute constraint on the audio input.

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 a specific verb and resource: transcribe audio with Whisper large v3 turbo. It names the supported format set, source options, and the alternative translate-into-English task, so an agent can distinguish it from text-translation siblings without opening the schema.

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 through formats, size limits, and URL/base64 input, but it never explicitly says when to choose this over translate_text or other siblings. Guidance is present but implicit rather than routing-level.

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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