Whissle MCP Server

speech_to_text

Convert speech to text using a selected ASR model, save transcriptions with optional timestamps and word boosts, and store output files in a specified directory. Includes cost alerts for API usage.

Instructions

Convert speech to text with a given model and save the output text file to a given directory. Directory is optional, if not provided, the output file will be saved to $HOME/Desktop.

⚠️ COST WARNING: This tool makes an API call to Whissle which may incur costs. Only use when explicitly requested by the user. Args: audio_file_path (str): Path to the audio file to transcribe model_name (str, optional): The name of the ASR model to use. Defaults to "en-NER" timestamps (bool, optional): Whether to include word timestamps boosted_lm_words (List[str], optional): Words to boost in recognition boosted_lm_score (int, optional): Score for boosted words (0-100) output_directory (str, optional): Directory where files should be saved. Defaults to $HOME/Desktop if not provided. Returns: TextContent with the transcription and path to the output file.

Input Schema

NameRequiredDescriptionDefault
audio_file_pathYes
boosted_lm_scoreNo
boosted_lm_wordsNo
model_nameNoen-NER
timestampsNo

Input Schema (JSON Schema)

{ "properties": { "audio_file_path": { "title": "Audio File Path", "type": "string" }, "boosted_lm_score": { "default": 80, "title": "Boosted Lm Score", "type": "integer" }, "boosted_lm_words": { "default": null, "items": { "type": "string" }, "title": "Boosted Lm Words", "type": "array" }, "model_name": { "default": "en-NER", "title": "Model Name", "type": "string" }, "timestamps": { "default": true, "title": "Timestamps", "type": "boolean" } }, "required": [ "audio_file_path" ], "title": "speech_to_textArguments", "type": "object" }

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