ElevenLabs MCP Server
# ElevenLabs MCP Server
[](https://smithery.ai/server/elevenlabs-mcp-server)
A Model Context Protocol (MCP) server that integrates with ElevenLabs text-to-speech API, featuring both a server component and a sample web-based MCP Client (SvelteKit) for managing voice generation tasks.
<a href="https://glama.ai/mcp/servers/leukzvus7o"><img width="380" height="200" src="https://glama.ai/mcp/servers/leukzvus7o/badge" alt="ElevenLabs Server MCP server" /></a>
## Features
- Generate audio from text using ElevenLabs API
- Support for multiple voices and script parts
- SQLite database for persistent history storage
- Sample SvelteKit MCP Client for:
- Simple text-to-speech conversion
- Multi-part script management
- Voice history tracking and playback
- Audio file downloads
## Installation
### Installing via Smithery
To install ElevenLabs MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/elevenlabs-mcp-server):
```bash
npx -y @smithery/cli install elevenlabs-mcp-server --client claude
```
### Using uvx (recommended)
When using [`uvx`](https://docs.astral.sh/uv/guides/tools/), no specific installation is needed.
Add the following configuration to your MCP settings file (e.g., `cline_mcp_settings.json` for Claude Desktop):
```json
{
"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
1. Clone this repository
2. Install dependencies:
```bash
uv venv
```
3. Copy `.env.example` to `.env` and fill in your ElevenLabs credentials
```json
{
"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"
}
}
}
}
```
## Using the Sample SvelteKit MCP Client
1. Navigate to the web UI directory:
```bash
cd clients/web-ui
```
2. Install dependencies:
```bash
pnpm install
```
3. Copy `.env.example` to `.env` and configure as needed
4. Run the web UI:
```bash
pnpm dev
```
5. Open http://localhost:5174 in your browser
### Available Tools
- `generate_audio_simple`: Generate audio from plain text using default voice settings
- `generate_audio_script`: Generate audio from a structured script with multiple voices and actors
- `delete_job`: Delete a job by its ID
- `get_audio_file`: Get the audio file by its ID
- `list_voices`: List all available voices
- `get_voiceover_history`: Get voiceover job history. Optionally specify a job ID for a specific job.
### Available Resources
- `voiceover://history/{job_id}`: Get the audio file by its ID
- `voiceover://voices`: List all available voices
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no ambiguity. delete_job removes jobs, generate_audio_script creates multi-voice audio from structured input, generate_audio_simple creates basic audio, get_audio_file retrieves audio content, get_voiceover_history accesses job history, and list_voices lists available voices. The two generation tools are clearly differentiated by complexity level.
All tools follow a consistent verb_noun pattern throughout: delete_job, generate_audio_script, generate_audio_simple, get_audio_file, get_voiceover_history, list_voices. The naming convention is perfectly uniform with clear action-object relationships and no mixing of styles.
Six tools is an ideal number for this audio generation domain. It provides complete coverage of core workflows (generation, retrieval, management, discovery) without being overwhelming. Each tool earns its place with clear utility in the voiceover job lifecycle.
The toolset provides complete CRUD/lifecycle coverage for ElevenLabs voiceover operations: create (two generation tools), read (get_audio_file, get_voiceover_history, list_voices), delete (delete_job). There are no obvious gaps - agents can create audio, retrieve results, manage jobs, and discover available voices.