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MCP for Claude & ChatGPT

by com.tuqui
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Transcribe an audio

audio_transcribe
Read-only

Transcribe an audio file on your disk (a voice note, a call, a meeting) to text. Returns a one-use URL and a curl command; run it and the response is {"text": ...}. The file never passes through the conversation. A long audio takes minutes: save the response to a file (curl -o) and read it in parts. Up to 25 MB (mp3, m4a, ogg, webm, wav, flac). Spends from the chat budget when the file arrives. For an audio attached to an Odoo record, use odoo_attachment_content. It does not read an audio on Google Drive: download it first.

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": "audio_transcribe"
  }
}

Input Schema

NameRequiredDescriptionDefault
filenameNoThe path of the audio file, to fill in the curl command.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Goes far beyond the annotations by disclosing the unusual return mechanism (one-use URL plus curl command), that the file never passes through the conversation, the latency profile for long audio, size/format limits, and that it spends from the chat budget. These are exactly the behavioral traits an agent cannot infer from readOnlyHint/openWorldHint.

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?

Dense but tight prose: purpose first, then return mechanism, then operational caveats, then format limits, then sibling routing and exclusions. Every sentence carries actionable information with no filler.

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?

No output schema exists, yet the description explains the return value ({'text': ...} after running the curl command), the one-use URL mechanism, size and format limits, latency expectations, and cost implications. An agent has everything needed to invoke and consume the result 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?

With a single parameter and 100% schema description coverage, the baseline is 3. The description adds meaningful constraints on the filename's acceptable inputs (up to 25 MB; mp3, m4a, ogg, webm, wav, flac) and reiterates that the path is used to fill in the curl command, which gives more than the schema alone.

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?

States a specific verb and resource ('Transcribe an audio file on your disk... to text') and immediately distinguishes scope by naming what it is not: 'For an audio attached to an Odoo record, use odoo_attachment_content' and 'It does not read an audio on Google Drive'. An agent can select it 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 Guidelines5/5

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

Explicitly names alternatives and the conditions that select them: odoo_attachment_content for Odoo attachments, and downloading first for Google Drive files. It also gives a workflow instruction (save the response to a file and read it in parts for long audio), leaving little to inference.

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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