get_audio_file
Retrieve generated audio files from ElevenLabs text-to-speech jobs using the job ID to access and download speech content.
Instructions
Get the audio file content for a specific job
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | ID of the job to get audio file for |
Implementation Reference
- src/elevenlabs_mcp/server.py:267-280 (registration)Registration of the 'get_audio_file' tool including its input schema definition.
types.Tool( name="get_audio_file", description="Get the audio file content for a specific job", inputSchema={ "type": "object", "properties": { "job_id": { "type": "string", "description": "ID of the job to get audio file for" } }, "required": ["job_id"] } ), - src/elevenlabs_mcp/server.py:569-612 (handler)Implementation of the get_audio_file tool handler: fetches job from database, reads the output audio file, base64 encodes it, and returns as an embedded resource.
elif name == "get_audio_file": job_id = arguments.get("job_id") if not job_id: raise ValueError("job_id is required") # Get job to check if it exists and get file path job = await self.db.get_job(job_id) if not job: return [types.TextContent( type="text", text=f"Job {job_id} not found" )] if not job.output_file: return [types.TextContent( type="text", text=f"No output file found for job {job_id}" )] # Check if file exists output_path = Path(job.output_file) if not output_path.exists(): return [types.TextContent( type="text", text=f"Output file not found at {job.output_file}" )] # Read the audio file and encode it as base64 with open(output_path, 'rb') as f: audio_bytes = f.read() audio_base64 = base64.b64encode(audio_bytes).decode('utf-8') # Return the audio file content return [ types.EmbeddedResource( type="resource", resource=types.BlobResourceContents( uri=f"audio://{output_path.name}", name=output_path.name, blob=audio_base64, mimeType="audio/mpeg" ) ) ]