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abid-mahdi

whisper-telegram-mcp

by abid-mahdi
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
WHISPER_MODELNoWhisper model size to use for local inference (e.g., tiny, base, small, medium, large-v3, turbo).base
OPENAI_API_KEYNoOpenAI API key. Required if using the 'openai' backend.
WHISPER_BACKENDNoTranscription backend to use: 'auto' (tries local first, falls back to OpenAI), 'local' (faster-whisper), or 'openai' (Whisper API).auto
WHISPER_LANGUAGENoISO-639-1 language code (e.g., 'en'). Defaults to auto-detection if not specified.
TELEGRAM_BOT_TOKENNoTelegram Bot API token. Required for the transcribe_telegram_voice tool.

Capabilities

Features and capabilities supported by this server

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

Tools

Functions exposed to the LLM to take actions

NameDescription
transcribe_audioA

Transcribe an audio file to text using Whisper.

Supports OGG (Telegram voice), WAV, MP3, FLAC, and most common audio formats.

Args: file_path: Absolute path to the audio file to transcribe. language: Optional ISO-639-1 language code (e.g. 'en', 'fr'). None = auto-detect. word_timestamps: If True, include word-level timestamps in segments.

Returns: dict with: text, language, language_probability, duration, segments, backend, success, error

transcribe_telegram_voiceA

Download and transcribe a Telegram voice message.

Downloads the voice message from Telegram, transcribes it, then deletes the temp file.

Args: file_id: The file_id from a Telegram voice message (from the Message object). bot_token: Telegram bot token. Falls back to TELEGRAM_BOT_TOKEN env var. language: Optional ISO-639-1 language code. None = auto-detect. word_timestamps: Include word-level timestamps in segments.

Returns: Same dict structure as transcribe_audio.

list_modelsB

List available Whisper model sizes with performance characteristics.

Configure the active model via the WHISPER_MODEL environment variable. Default is 'base' -- a good balance of speed and accuracy for voice messages.

check_backendsA

Check which transcription backends are available and configured.

Call this first to verify your setup before transcribing.

speak_textA

Convert text to speech and return an OGG/Opus audio file path.

Plays as a native voice note in Telegram when sent as an attachment.

TTS backends (in priority order):

  1. Kokoro (local, free, natural-sounding) -- auto-starts via uvx kokoro-fastapi

  2. OpenAI TTS (cloud, requires OPENAI_API_KEY, ~$0.015/1k chars)

  3. macOS say (Mac only fallback, sounds robotic)

Configure via TTS_BACKEND env var: "auto" | "kokoro" | "openai" | "macos"

Args: text: Text to synthesise. voice: Voice name. Kokoro voices: af_sky, af_bella, af_sarah, am_adam, am_michael, bf_emma, bm_george, bm_lewis. OpenAI voices: alloy, echo, fable, onyx, nova, shimmer. Configure default via TTS_VOICE env var. output_path: Optional absolute path for the output .ogg file.

Returns: dict with: file_path (absolute .ogg path), backend, voice, success, error

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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