ElevenLabs MCP Server: Seamless Integration of Text-to-Speech with AI Applications

Overview: What is ElevenLabs MCP Server?

The ElevenLabs MCP Server is an advanced infrastructure solution designed to bridge the gap between Model Context Protocol (MCP) compliant AI applications and external data sources. By integrating with ElevenLabs' text-to-speech API, this server enables seamless voice generation for a wide range of applications, including but not limited to chatbots, avatars, and virtual assistants. The core value proposition lies in its ability to enhance the capabilities of these AI applications through real-time, customizable audio output.

🔧 Core Features & MCP Capabilities

The ElevenLabs MCP Server delivers a robust set of features designed to meet the demands of modern AI development:

Text-to-Speech Conversion: Convert plain text and structured scripts into high-quality audio files.
Voice Customization: Supports multiple voices with adjustable stability, similarity boost, and style parameters for fine-grained control over voice output.
Persistent History Storage: Utilize SQLite for storing historical data, enabling easy retrieval of past tasks and jobs.
Sample MCP Client (SvelteKit): Provides a web-based interface to manage text-to-speech conversion tasks. It includes functionalities such as simple text-to-speech generation, multi-part script management, and voice history tracking.

⚙️ MCP Architecture & Protocol Implementation

The server is built around the Model Context Protocol (MCP) framework, ensuring compatibility with various AI applications including Claude Desktop, Continue, and Cursor. The implementation includes:

Command-Like Interface: Accepts commands similar to those used by other MCP servers.
Configuration Flexibility: Allows customization through environment variables for flexibility in setting up different instances.

The protocol flow is designed to be versatile, ensuring seamless integration with ElevenLabs' API while maintaining compatibility with the broader MCP ecosystem:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[ElevenLabs API]
    style A fill:#e1f5fe
    style B fill:#ffffff
    style C fill:#f3e5f5
    style D fill:#effbff

🚀 Getting Started with Installation

To get started, you can choose between two installation methods:

Using uvx (Recommended)

When using uvx, no separate installation is required. Simply add the following configuration to your MCP settings file for Claude Desktop:

{
  "mcpServers": {
    "elevenlabs": {
      "command": "uvx",
      "args": ["elevenlabs-mcp-server"],
      "env": {
        "ELEVENLABS_API_KEY": "your-api-key",
        "ELEVENLABS_VOICE_ID": "your-voice-id",
        "ELEVENLABS_MODEL_ID": "eleven_flash_v2",
        "ELEVENLABS_STABILITY": "0.5",
        "ELEVENLABS_SIMILARITY_BOOST": "0.75",
        "ELEVENLABS_STYLE": "0.1",
        "ELEVENLABS_OUTPUT_DIR": "output"
      }
    }
  }
}

Development Installation

For detailed setup, follow these steps:

Clone the repository:

git clone https://github.com/your-repo-url.git

Install dependencies:
```
uv venv
```
Configure environment variables:
- Copy .env.example to .env and fill in your credentials.

💡 Key Use Cases in AI Workflows

Real-World Scenario 1: Chatbot Integration

Imagine a chatbot that needs to respond dynamically based on user inputs, providing human-like voices for more engaging conversations. By integrating the ElevenLabs MCP Server, this chatbot can leverage pre-registered voices and StabilityAI models, ensuring smooth real-time text-to-speech conversion.

Real-World Scenario 2: Virtual Assistant Simulation

In a virtual assistant application, users might request specific information or initiate tasks based on predefined scripts. The TwelveLabs MCP Server enables the assistant to handle these scenarios by utilizing multiple voices for different actors in the script, ensuring a more natural and responsive user experience.

🔌 Integration with MCP Clients

The ElevenLabs MCP Server features a sample SvelteKit client that facilitates web-based interaction, providing functionalities such as:

Generate Audio from Plain Text: Quickly generate audio files using simple text inputs.
Multi-Part Script Management: Handle complex scripts with multiple voices and actors.
Voice History Tracking & Playback: Keep track of historical jobs for easy retrieval and relaunching.
Audio File Downloads: Easily download generated audio files for further use.

📊 Performance & Compatibility Matrix

The following table outlines the compatibility matrix with various MCP clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌ (Limited compatibility)	☑️	❌ (Partial support)	Tools Only, Partial Functionality

🛠️ Advanced Configuration & Security

For advanced setup and security considerations:

Custom Environment Variables: Adjust the environment variables to tailor the server to your specific needs.
API Key Management: Ensure secure handling of API keys by maintaining them in a safe location outside the codebase.

Example configuration snippet:

{
  "mcpServers": {
    "elevenlabs": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/elevenlabs-mcp-server",
        "run",
        "elevenlabs-mcp-server"
      ],
      "env": {
        "ELEVENLABS_API_KEY": "your-api-key",
        "ELEVENLABS_VOICE_ID": "your-voice-id",
        "ELEVENLABS_MODEL_ID": "eleven_flash_v2",
        "ELEVENLABS_STABILITY": "0.5",
        "ELEVENLABS_SIMILARITY_BOOST": "0.75",
        "ELEVENLABS_STYLE": "0.1",
        "ELEVENLABS_OUTPUT_DIR": "output"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

Q: Can I use this server with multiple AI applications?

A: Yes, the server is compatible with various MCP clients such as Claude Desktop and Continue, providing a unified interface for text-to-speech conversion.

Q: What API key management practices should I follow?

A: Store your API keys securely using environment variables or encrypted files to avoid exposing sensitive information in plaintext.

Q: How do I configure the server for a specific voice?

A: Customize the ELEVENLABS_VOICE_ID and related environment variables to select the appropriate voice tone, stability settings, and output directory.

Q: What are the performance benefits of using SQLite for history storage?

A: SQLite provides fast in-memory storage capabilities that ensure efficient job tracking and quick data retrieval, enhancing overall server performance.

Q: How can I troubleshoot issues with script generation?

A: Common errors may arise from incorrect API key usage or misconfigured environment variables. Verify these settings to resolve any script generation issues.

👨‍💻 Development & Contribution Guidelines

To contribute to the ElevenLabs MCP Server:

Fork the repository.
Follow the coding standards and commit message guidelines.
Submit a pull request for review.

🌐 MCP Ecosystem & Resources

For more information about Model Context Protocol and related resources, visit the official documentation and community forums. Explore other MCP server implementations to expand knowledge and integrate additional functionalities.

This comprehensive guide positions the ElevenLabs MCP Server as a powerful tool for developers building AI applications that require seamless text-to-speech integration. With its rich feature set and robust compatibility matrix, it enhances the user experience across various applications while ensuring smooth MCP protocol adherence.

ElevenLabs MCP Server