MCPGeneration-for-ElevenLabs
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- AlicenseAqualityDmaintenanceA full-featured MCP server for the ElevenLabs API that brings text-to-speech, speech-to-text, voice cloning, sound effects, music, audio isolation, dubbing, and account tools to any MCP client.28MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that provides text-to-speech, speech-to-text, and voice management via ElevenLabs API.1MIT
- AlicenseNot gradedqualityDmaintenanceOfficial MCP server that enables interaction with ElevenLabs Text to Speech and audio processing APIs. It allows generating speech, cloning voices, transcribing audio, and creating sound effects through natural language.MIT
- AlicenseAqualityDmaintenanceAn MCP server that enables voice-to-voice AI conversations using ElevenLabs for speech synthesis and recognition, with tools for voice management, text-to-speech, and speech-to-text.7MIT

ElevenLabs MCP Serverofficial
AlicenseBqualityFmaintenanceAn official Model Context Protocol (MCP) server that enables AI clients to interact with ElevenLabs' Text to Speech and audio processing APIs, allowing for speech generation, voice cloning, audio transcription, and other audio-related tasks.271,544MIT- AlicenseNot gradedqualityBmaintenanceA local MCP server that turns any text into narration, voice-overs, dialogues, audiobook chapters and per-shot video clips as MP3/WAV files — with emotions, acting modes, inline cues, presets and subtitles — driven by a ChatGPT sign-in rather than an API key. It also exposes tools for inspecting audio (timings, pace, pitch, waveform), transcribing recordings, listing and favouring voices, saving pronunciation presets, and checking sign-in status.MIT
TDQS
Scored across 89 tools
The server has many intentionally parallel tools, especially non-streaming vs streaming vs timestamped variants for speech, dialogue, and music, plus several usage/budget/history read tools. Descriptions usually clarify boundaries, but the sheer number of near-duplicate generation paths makes misselection likely for an agent.
Tool names consistently use snake_case verb_noun patterns such as generate_speech, list_voices, get_asset, delete_asset, and update_voice_settings. Minor suffixes like _stream and _with_timestamps are predictable and coherent.
Eighty-nine tools is an extreme mismatch for a single MCP server, even one covering a broad media API. It far exceeds the practical 3-15 range and creates a large selection burden, duplicate pathways, and cognitive overhead.
The surface covers a very wide domain: TTS, dialogue, sound effects, music, dubbing, voices, history, assets, image/video generation, flows, and local FFmpeg operations. There are only minor lifecycle gaps, such as limited update operations for some resources, but no major dead ends.