About
A Model Context Protocol server that integrates with the ElevenLabs text‑to‑speech API, offering voice generation, multi‑part script handling, and a SvelteKit client for managing jobs and playback. It stores history in SQLite for easy retrieval.
Capabilities
The ElevenLabs MCP Server bridges the gap between conversational AI assistants and high‑quality text‑to‑speech services. By exposing ElevenLabs’ robust API through the Model Context Protocol, it allows assistants such as Claude to generate spoken audio directly from user prompts or structured scripts without leaving the chat interface. This integration solves a common pain point for developers: the need to handle external TTS services, manage voice selections, and store playback history in a single, cohesive workflow.
At its core, the server accepts simple text or complex script objects and returns synthesized audio files. It supports a range of voice parameters—including stability, similarity boost, style, and model selection—so developers can fine‑tune the naturalness and character of each utterance. The server also maintains a SQLite database that records every job, enabling easy retrieval and playback of past voiceovers. This persistent history is invaluable for debugging, auditing, or re‑using previously generated audio.
Key capabilities include:
- Multi‑voice script rendering: Handlers can specify different actors and voices within a single script, making it ideal for dialogues or narrated stories.
- Job management tools: Endpoints such as and let clients clean up or fetch specific recordings on demand.
- Voice discovery: The tool returns all voices available to the configured ElevenLabs account, simplifying dynamic UI generation.
- Web‑based client: A lightweight SvelteKit demo demonstrates how to convert text, manage multi‑part scripts, and download or play back audio—all through the MCP interface.
In real‑world scenarios, this server is a natural fit for voice‑enabled chatbots, interactive tutorials, podcast production pipelines, and accessibility features that require spoken output. Developers can embed the MCP client in their own applications or leverage the sample web UI to prototype quickly. Because the server runs locally and communicates over standard MCP endpoints, it preserves privacy while still offering cloud‑scale TTS quality. Its modular design also means that swapping out ElevenLabs for another provider is straightforward, ensuring long‑term flexibility.
Related Servers
Netdata
Real‑time infrastructure monitoring for every metric, every second.
Awesome MCP Servers
Curated list of production-ready Model Context Protocol servers
JumpServer
Browser‑based, open‑source privileged access management
OpenTofu
Infrastructure as Code for secure, efficient cloud management
FastAPI-MCP
Expose FastAPI endpoints as MCP tools with built‑in auth
Pipedream MCP Server
Event‑driven integration platform for developers
Weekly Views
Server Health
Information
Explore More Servers
JBang MCP Server
Run, test, and deploy Model Context Protocol services with ease
Solana Docs MCP Server
Simple notes system for Solana docs
Myshoes MCP Server
JSON‑RPC server for managing Myshoes data via MCP
LG Therma V MCP Server
Control LG Therma V heat pumps via Model Context Protocol
Mcp Python Demo Server
Fast, file‑centric MCP server with dynamic greetings
HagaiHen/facebook-mcp-server
MCP Server: HagaiHen/facebook-mcp-server