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elevenlabs-mcp

Generate speech, transcribe audio, create voice agents, compose music, and manage voices using ElevenLabs MCP Server. Use when working with text-to-speech, speech-to-text, voice cloning, conversational AI agents, or music composition.

Quellinformationen

Repository
pmarashian/cursor-agent-skills
Letzte Quellaktivität
13. Februar 2026 um 19:51
Erkannte Sprache von SKILL.md
Englisch
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2
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1

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
elevenlabs-mcp
description
Generate speech, transcribe audio, create voice agents, compose music, and manage voices using ElevenLabs MCP Server. Use when working with text-to-speech, speech-to-text, voice cloning, conversational AI agents, or music composition.
tags
["audio","text-to-speech","speech-to-text","voice-cloning","ai-agents","music-composition","audio-processing"]
# ElevenLabs MCP Server Generate speech, transcribe audio, create voice agents, compose music, and manage voices using the ElevenLabs MCP Server. ## Overview The ElevenLabs MCP Server provides comprehensive tools for audio generation, transcription, voice management, conversational AI agents, and music composition. Many operations **incur API costs** - only use when explicitly requested by the user. **Server:** ElevenLabs MCP (configured via MCP settings) ## Setup The MCP server is already configured and enabled. You can call these tools directly - they will be available in your tool list. ## ⚠️ CRITICAL: Cost Warnings **MANY TOOLS INCUR API COSTS** - Only use when explicitly requested by the user: - Text-to-Speech (TTS) operations - Speech-to-Text (STT) operations - Voice cloning - Agent creation and conversations - Music composition - Audio processing (isolate, speech-to-speech) - Outbound phone calls **Always check with the user before using cost-incurring tools unless they explicitly request them.** ## Core Capabilities ### Text-to-Speech (TTS) - Convert text to natural-sounding speech - Multiple voice options (search, list, or use voice IDs) - Various models (multilingual, flash, turbo) - Adjustable parameters (stability, similarity, speed, style) - Multiple output formats (MP3, PCM, Opus, μ-law, A-law) ### Speech-to-Text (STT) - Transcribe audio files to text - Automatic language detection - Speaker diarization (identify different speakers) - Support for various audio formats ### Text-to-Sound Effects - Generate sound effects from text descriptions - Configurable duration (0.5-5 seconds) - Loop option for continuous playback - Multiple output formats ### Voice Management - Search and browse voice library - Clone voices from audio samples - Create custom voices from text descriptions - Get voice details and metadata - List available voices ### Conversational AI Agents - Create voice-enabled conversational agents - Configure system prompts and first messages - Add knowledge bases (PDF, DOCX, TXT, HTML, EPUB) - Make outbound phone calls - Manage conversations and transcripts - Support for multiple LLM backends ### Music Composition - Generate music from text prompts - Create composition plans for structured music - Control style, sections, and duration - Multiple output formats ### Audio Processing - Isolate audio from files - Transform speech between voices (speech-to-speech) - Play audio files (WAV, MP3) ### Phone Integration - List phone numbers - Make outbound calls using agents - Automatic provider detection (Twilio or SIP trunk) ## Available Tools ### Text-to-Speech Tools - `text_to_speech` - Convert text to speech with voice selection - `text_to_voice` - Create voice previews from text prompts (generates 3 variations) - `create_voice_from_preview` - Add generated voice to library ### Speech-to-Text Tools - `speech_to_text` - Transcribe audio files to text - `speech_to_speech` - Transform audio from one voice to another ### Sound Effects Tools - `text_to_sound_effects` - Generate sound effects from descriptions ### Voice Management Tools - `search_voices` - Search your voice library - `search_voice_library` - Search entire ElevenLabs voice library - `get_voice` - Get details of a specific voice - `voice_clone` - Create instant voice clone from audio files ### Agent Tools - `create_agent` - Create a conversational AI agent - `add_knowledge_base_to_agent` - Add knowledge base to agent - `list_agents` - List all your agents - `get_agent` - Get agent details - `get_conversation` - Get conversation transcript - `list_conversations` - List agent conversations ### Music Tools - `compose_music` - Generate music from prompt or composition plan - `create_composition_plan` - Create structured composition plan ### Audio Processing Tools - `isolate_audio` - Isolate audio from a file - `play_audio` - Play audio files (WAV, MP3) ### Phone Tools - `list_phone_numbers` - List phone numbers - `make_outbound_call` - Make outbound call using agent ### Utility Tools - `list_models` - List available TTS models - `check_subscription` - Check subscription status and usage ## Text-to-Speech Workflow ### Basic TTS ```python # Simple text-to-speech result = text_to_speech( text="Hello, this is a test of text-to-speech.", voice_name="Adam", # or use voice_id output_directory="./output" ) # Returns file path to generated audio ``` ### Voice Selection You can use either `voice_name` or `voice_id`: ```python # Using voice name text_to_speech(text="Hello", voice_name="Adam") # Using voice ID text_to_speech(text="Hello", voice_id="cgSgspJ2msm6clMCkdW9") # Search for voices first voices = search_voices(search="male professional") voice_id = voices[0]["voice_id"] text_to_speech(text="Hello", voice_id=voice_id) ``` ### Model Selection Available models: - `eleven_multilingual_v2` - High quality multilingual (29 languages) - `eleven_flash_v2_5` - Fastest, ultra-low latency (32 languages) - `eleven_turbo_v2_5` - Balanced quality and speed (32 languages) - `eleven_flash_v2` - Fast English-only - `eleven_turbo_v2` - Balanced English-only - `eleven_monolingual_v1` - Legacy English ```python text_to_speech( text="Hello", model_id="eleven_multilingual_v2", language="en" ) ``` ### TTS Parameters Key parameters for fine-tuning: - `stability` (0-1): Voice stability vs. emotional range (default: 0.5) - `similarity_boost` (0-1): Adherence to original voice (default: 0.75) - `style` (0-1): Style exaggeration (default: 0) - `use_speaker_boost` (bool): Boost similarity to original speaker (default: true) - `speed` (0.7-1.2): Speech speed (default: 1.0) - `output_format`: Audio format (default: "mp3_44100_128") ## Speech-to-Text Workflow ### Basic Transcription ```python # Transcribe audio file result = speech_to_text( input_file_path="./audio/recording.mp3", save_transcript_to_file=True, output_directory="./transcripts" ) # Returns transcript text and saves to file ``` ### With Diarization ```python # Transcribe with speaker identification result = speech_to_text( input_file_path="./audio/meeting.mp3", diarize=True, # Identify different speakers return_transcript_to_client_directly=True ) # Returns transcript with speaker annotations ``` ### Language Detection ```python # Automatic language detection (default) speech_to_text(input_file_path="./audio.mp3") # Specify language speech_to_text( input_file_path="./audio.mp3", language_code="es" # ISO 639-3 code ) ``` ## Voice Cloning Workflow ### Clone from Audio Files ```python # Clone voice from audio samples result = voice_clone( name="My Custom Voice", files=[ "./samples/sample1.mp3", "./samples/sample2.mp3", "./samples/sample3.mp3" ], description="Professional male voice" ) # Returns voice_id for use in TTS ``` ### Create Voice from Text Description ```python # Generate voice previews previews = text_to_voice( voice_description="A warm, friendly female voice with a slight British accent", text="Hello, this is a preview of the generated voice." ) # Returns 3 preview variations with generated_voice_id # Add to library create_voice_from_preview( generated_voice_id=previews["generated_voice_id"], voice_name="Friendly British Voice", voice_description="Warm, friendly female voice with British accent" ) ``` ## Agent Creation Workflow ### Basic Agent ```python # Create conversational AI agent agent = create_agent( name="Customer Support Agent", first_message="Hi, how can I help you today?", system_prompt="You are a helpful customer support agent...", voice_id="cgSgspJ2msm6clMCkdW9", language="en" ) # Returns agent_id ``` ### Agent with Knowledge Base ```python # Create agent first agent_id = create_agent(...)["agent_id"] # Add knowledge base add_knowledge_base_to_agent( agent_id=agent_id, knowledge_base_name="Product Documentation", input_file_path="./docs/product_manual.pdf" ) # Or add from URL add_knowledge_base_to_agent( agent_id=agent_id, knowledge_base_name="Company Website", url="https://example.com/docs" ) # Or add from text add_knowledge_base_to_agent( agent_id=agent_id, knowledge_base_name="FAQ", text="Q: What is your return policy? A: 30 days..." ) ``` ### Making Outbound Calls ```python # List available phone numbers phone_numbers = list_phone_numbers() # Make outbound call make_outbound_call( agent_id=agent_id, agent_phone_number_id=phone_numbers[0]["id"], to_number="+1234567890" # E.164 format ) ``` ### Managing Conversations ```python # List conversations conversations = list_conversations( agent_id=agent_id, page_size=30 ) # Get conversation transcript transcript = get_conversation( conversation_id=conversations[0]["conversation_id"] ) ``` ## Music Composition Workflow ### Basic Music Generation ```python # Generate music from prompt music = compose_music( prompt="Upbeat electronic dance music with synthesizers", music_length_ms=60000, # 60 seconds output_directory="./music" ) # Returns file path to generated music ``` ### Structured Composition Plan ```python # Create composition plan first plan = create_composition_plan( prompt="Epic orchestral piece with multiple movements", music_length_ms=180000 # 3 minutes ) # Generate music from plan music = compose_music( composition_plan=plan, output_directory="./music" ) ``` ## Audio Processing Workflow ### Isolate Audio ```python # Isolate audio from file (remove background noise) isolated = isolate_audio( input_file_path="./audio/with_background.mp3", output_directory="./audio/isolated" ) ``` ### Speech-to-Speech Voice Transformation ```python # Transform audio to different voice transformed = speech_to_speech( input_file_path="./audio/original.mp3", voice_name="Adam", output_directory="./audio/transformed" ) ``` ### Play Audio ```python # Play audio file (WAV or MP3) play_audio(input_file_path="./audio/sample.mp3") ``` ## Sound Effects Generation ```python # Generate sound effect sound_effect = text_to_sound_effects( text="Door creaking open slowly", duration_seconds=2.0, loop=False, output_directory="./sounds" ) ``` ## Key Parameters Reference ### text_to_speech - `text` (required): Text to convert - `voice_name` or `voice_id`: Voice selection - `model_id`: TTS model (default: eleven_multilingual_v2) - `stability` (0-1): Voice stability - `similarity_boost` (0-1): Voice similarity - `speed` (0.7-1.2): Speech speed - `output_format`: Audio format - `output_directory`: Save location (default: $HOME/Desktop) ### speech_to_text - `input_file_path` (required): Audio file to transcribe - `diarize` (bool): Enable speaker diarization - `language_code`: ISO 639-3 language code (auto-detect if omitted) - `save_transcript_to_file` (bool): Save transcript to file - `return_transcript_to_client_directly` (bool): Return text directly ### create_agent - `name` (required): Agent name - `first_message` (required): First message agent says - `system_prompt` (required): System prompt - `voice_id`: Voice for agent (default: cgSgspJ2msm6clMCkdW9) - `language`: ISO 639-1 code (default: "en") - `llm`: LLM backend (default: "gemini-2.0-flash-001") - `temperature` (0-1): Response randomness - `max_duration_seconds`: Max conversation length (default: 300) ### compose_music - `prompt` or `composition_plan` (required): Music description or plan - `music_length_ms`: Duration in milliseconds - `output_directory`: Save location (default: $HOME/Desktop) ## Best Practices ### Cost Management - **Always check subscription status** before running multiple operations - Use `check_subscription()` to monitor usage - Only use cost-incurring tools when explicitly requested - Consider using faster/cheaper models when quality requirements are lower ### File Handling **File Output Behavior**: - Files are **always written to `$HOME/Desktop`** regardless of `output_directory` parameter - The `output_directory` parameter is **ignored** - File naming: `{description}_{timestamp}.mp3` - Must manually move files to project directory
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