ElevenLabs MCP Server

ElevenLabs MCP Server – Overview

The ElevenLabs MCP Server bridges the gap between AI assistants and high‑quality, customizable text‑to‑speech (TTS) output. By exposing ElevenLabs’ TTS API as an MCP service, it allows Claude and other agents to generate spoken audio directly from natural language prompts or structured scripts. This solves the common developer pain point of having to manually call a separate TTS service, manage authentication, and handle audio file storage—all while keeping the workflow fully integrated within the MCP ecosystem.

At its core, the server accepts a set of well‑defined tools that let clients request simple text conversions or complex multi‑voice scripts. The tool wraps a single API call, turning plain text into an MP3 file using default voice parameters. For richer productions, parses a script object containing multiple actors and voice IDs, orchestrating parallel requests to ElevenLabs and stitching the resulting clips into a single coherent audio track. In addition, utility tools such as , , and provide full lifecycle management of audio assets, while the resource offers a convenient history view that can be queried by job ID or retrieved in bulk.

Persistence is handled via an SQLite database, ensuring that every voiceover job, its metadata, and the resulting file path are stored reliably. This history can be accessed through the MCP client or programmatically, enabling features like audit trails, repeat playback, and automated archival. The server also exposes a small web‑based client built with SvelteKit, which demonstrates the full range of tools and resources: users can submit text or scripts, view generated audio in a timeline, replay past jobs, and download files with a single click. This demo UI serves both as a quick test harness and a reference implementation for developers building their own interfaces.

Developers benefit from the server’s tight integration with existing AI workflows. An assistant can request a voiceover as part of a conversational turn, embed the resulting audio URL in its response, or trigger batch TTS jobs for podcasts and educational content. Because the MCP server handles authentication via environment variables, sensitive ElevenLabs credentials never leave the host machine, keeping deployments secure. The modular tool set also allows teams to extend or replace individual functions without affecting the overall contract, making it straightforward to swap in alternative TTS providers or add post‑processing steps such as noise reduction.

Unique advantages of this MCP implementation include its native support for multi‑voice scripts, which is rarely offered in other TTS integrations, and the built‑in history tracking that eliminates the need for external logging systems. By delivering a ready‑to‑use, fully documented MCP server with a polished client demo, the ElevenLabs MCP Server empowers developers to embed lifelike speech synthesis into AI assistants with minimal friction and maximum flexibility.