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arcaputo3

MCP Server Whisper

by arcaputo3
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OPENAI_API_KEYYesYour OpenAI API key for accessing Whisper and GPT-4o models
AUDIO_FILES_PATHYesPath to your audio files directory

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_latest_audioA

Get the most recent audio file from the audio path. ONLY USE THIS IF THE USER ASKS FOR THE LATEST FILE.

list_audio_filesC

List, filter, and sort audio files from the audio path. Supports regex pattern matching, filtering by metadata (size, duration, date, format), and sorting.

convert_audioB

A tool used to convert audio files to mp3 or wav which are gpt-4o compatible.

compress_audioA

A tool used to compress audio files which are >25mb. ONLY USE THIS IF THE USER REQUESTS COMPRESSION OR IF OTHER TOOLS FAIL DUE TO FILES BEING TOO LARGE.

transcribe_audioC

A tool used to transcribe audio files. It is recommended to use gpt-4o-mini-transcribe by default. If the user wants maximum performance, use gpt-4o-transcribe. Rarely should you use whisper-1 as it is least performant, but it is available if needed. You can use prompts to guide the transcription process based on the users preference.

chat_with_audioC

A tool used to chat with audio files. The response will be a response to the audio file sent. It is recommended to use gpt-4o-audio-preview by default for best results. Note: gpt-4o-mini-audio-preview has limitations with audio chat and may not process audio correctly.

transcribe_with_enhancementB

Transcribe audio with GPT-4 using specific enhancement prompts.

    Enhancement types:
    - detailed: Provides detailed description including tone, emotion, and background
    - storytelling: Transforms the transcription into a narrative
    - professional: Formats the transcription in a formal, business-appropriate way
    - analytical: Includes analysis of speech patterns, key points, and structure

    Args:
        input_file_name: Name of the input audio file to process
        enhancement_type: Type of enhancement to apply to the transcription
        model: The transcription model to use
        response_format: The response format
        timestamp_granularities: Optional timestamp granularities

    Returns:
    -------
        TranscriptionResult with enhanced transcription
create_audioC

Create text-to-speech audio using OpenAI's TTS API with model and voice selection.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.4/5.0

Scored across 8 tools

Disambiguation3/5

Most tools have clear single-action purposes (convert, compress, chat, create, list, get-latest), but transcribe_audio and transcribe_with_enhancement are very similar in function and could be easily confused, despite the enhancement descriptor. Descriptions and usage clues help, but the overlapping transcription surface creates some misselection risk.

Naming Consistency4/5

Tool names generally follow a verb_noun pattern in lowercase snake_case (list_audio_files, convert_audio, compress_audio, create_audio). Slight deviations exist with get_latest_audio, chat_with_audio, and transcribe_with_enhancement, which break the clean noun-object structure, but the pattern remains readable and predictable.

Tool Count5/5

Eight tools cover the full audio processing workflow—file access, format preparation, size handling, transcription, enhanced transcription, chat, and TTS—without unnecessary redundancy. Each tool earns its place and the count is well within the ideal range for a focused MCP server.

Completeness4/5

The surface is quite complete for a Whisper/audio media server: it supports listing, retrieving, converting, compressing, transcribing, enhanced transcription, audio chat, and TTS synthesis. Minor gaps such as no audio preview or batch processing exist, but agents can work around them with available tools.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources