MCP Server Whisper

"""MCP tools for text-to-speech operations.""" from typing import Optional from openai.types.audio.speech_model import SpeechModel from ..config import check_and_get_audio_path from ..constants import TTSVoice from ..infrastructure import FileSystemRepository, MCPServer, OpenAIClientWrapper, SecurePathResolver from ..models import TTSResult from ..services import TTSService def create_tts_tools(mcp: MCPServer) -> None: """Register TTS tools with the MCP server. Args: ---- mcp: FastMCP server instance. """ # Initialize services audio_path = check_and_get_audio_path() file_repo = FileSystemRepository(audio_path) openai_client = OpenAIClientWrapper() path_resolver = SecurePathResolver(audio_path) tts_service = TTSService(file_repo, openai_client, path_resolver) @mcp.tool(description="Create text-to-speech audio using OpenAI's TTS API with model and voice selection.") async def create_audio( text_prompt: str, model: SpeechModel = "gpt-4o-mini-tts", voice: TTSVoice = "alloy", instructions: Optional[str] = None, speed: float = 1.0, output_file_name: Optional[str] = None, ) -> TTSResult: """Generate text-to-speech audio from text prompts with customizable voices. Args: text_prompt: Text to convert to speech model: TTS model to use (gpt-4o-mini-tts is preferred) voice: Voice for the TTS (alloy, ash, coral, echo, fable, onyx, nova, sage, shimmer) instructions: Optional instructions for speech conversion (tonality, accent, style, etc.) speed: Speed of the speech conversion (0.25 to 4.0) output_file_name: Optional custom name for the output file (defaults to speech_<timestamp>.mp3) Returns: ------- TTSResult with name of the generated audio file Note: ---- Handles texts of any length by splitting into chunks at natural boundaries and concatenating the audio. OpenAI's TTS API has a limit of 4096 characters per request. """ return await tts_service.create_speech( text_prompt=text_prompt, output_filename=output_file_name, model=model, voice=voice, instructions=instructions, speed=speed, )