Whissle MCP Server

⚠️ 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" max_speakers (int, optional): Maximum number of speakers to identify 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 diarized transcription and path to the output file.

{ "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" }, "max_speakers": { "default": 2, "title": "Max Speakers", "type": "integer" }, "model_name": { "default": "en-NER", "title": "Model Name", "type": "string" } }, "required": [ "audio_file_path" ], "title": "diarize_speechArguments", "type": "object" }