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danielrosehill

Open Router Audio Transcription MCP

transcribe_audio

Transcribe audio files to text using OpenRouter. Select verbatim, cleaned, or custom modes to match your transcription needs.

Instructions

Transcribe an audio file using OpenRouter. Supports verbatim, cleaned, or custom prompt modes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesTranscription mode. 'verbatim': exact word-for-word transcription including filler words. 'cleaned': lightly edited for readability (removes fillers, adds punctuation, paragraph breaks). 'custom': use a custom prompt to direct the transcription.
modelNoOpenRouter model to use for transcription. Defaults to 'google/gemini-3-flash-preview'. Available models: xiaomi/mimo-v2-omni, google/gemini-3.1-flash-lite-preview, google/gemini-3-flash-preview, openai/gpt-audio, openai/gpt-audio-mini, mistralai/voxtral-small-24b-2507, openai/gpt-4o-audio-preview
budgetNoUse the default budget model instead of the standard model. Budget model: 'google/gemini-3.1-flash-lite-preview'. Ignored if 'model' is explicitly set.
file_pathYesAbsolute path to the audio file to transcribe. Supported formats: mp3, wav, ogg, flac, m4a, aac, webm, wma, opus
custom_promptNoCustom prompt to direct the transcription (required when mode is 'custom'). This replaces the default system prompt entirely.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full behavioral burden. It states the operation is a transcription and mentions modes but does not disclose whether it's synchronous (likely, given no job id), what format the output takes, whether it consumes tokens/budget, or error conditions (unsupported format, missing file). For a call to an external paid AI service, this is a significant transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the verb+resource. It's efficiently sized and wastes no words, though the second sentence only echoes enum values already in the schema.

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

Completeness2/5

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

A tool that hits an external AI service with a freeform custom_prompt path, budget/model selection, and no output schema deserves more: expected return shape (raw transcript? JSON?), sync vs async, cost behavior. The description covers neither return values nor operational behavior, leaving material gaps.

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?

Schema description coverage is 100% with rich enum descriptions for 'mode' and model lists for 'model', so the schema does the heavy lifting. The description's 'verbatim, cleaned, or custom prompt modes' repeats the enum values without adding semantics. Baseline 3 applies.

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

Purpose4/5

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

States a specific verb+resource: 'Transcribe an audio file'. The OpenRouter mention situates it as an external-service call, and the mode enumeration hints at behavior. It doesn't differentiate from the sibling list_transcription_models, but the sibling's name makes the boundary obvious.

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 via 'mode' options but never says when to choose this tool over alternatives, nor what prerequisites (audio access, file existence) exist. The sibling handles model listing, so the reader can infer a rough workflow but nothing is stated explicitly.

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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