"Using Docker for windsurfing-related applications or tools" matching MCP servers:

Enables AI agents to synthesize and play short summaries aloud while keeping full answers on screen, with queued speech and stop control using online natural voices or offline synthesis.

An MCP server implementation that integrates with Minimax API to provide AI-powered image generation and text-to-speech functionality in editors like Windsurf and Cursor.

A local stdio MCP server that enables validated access to official ElevenLabs APIs with cost controls, local media storage, and audio export for Godot.

Enables agents to access OpenAI-compatible transcription, live ASR, text-to-speech, voice cloning, phoneme recognition, and server-side file staging through streamable HTTP MCP tools.

Enables ChatGPT to generate ElevenLabs speech from text, returning playable MP3 audio, with voice listing and preference management.

Enables AI models to speak and sing using retro-style formant speech synthesis, converting text or phoneme strings to WAV audio via MCP tools.

Provides high-quality text-to-speech synthesis with 10 natural voices, emotion control, and dynamic pacing for professional applications requiring expressive speech output.

Enables access to a backend's native MCP tools and broader HTTP API for speech generation, voice cloning/design, transcription, dubbing, translation, subtitles, audiobooks, and related batch/long-form workflows over Streamable HTTP or local stdio.

Enables users to convert text into high-quality audio by accessing the OpenAI Text-to-Speech API. It supports customizable model selection and voice options for synthesized speech generation via the MCP protocol.

Provides access to Open Ai21 API services including chatbots (GPT-3.5, Claude 3, Llama 3), text-to-image generation, image background removal, text-to-speech, question answering, and text summarization capabilities.

Facilitates direct speech generation using Claude for multiple languages and emotions, integrating with a Zonos TTS setup via the Model Context Protocol.

An MCP server that lets an AI assistant turn written text — or prose it writes itself — into narrated audiobooks with chapter-marked .m4b files, using local Kokoro voices entirely offline and free. It supports 54 voices across 9 languages, adjustable speed, voice blending, and chapter-level resumable rendering.

A server that enables real-time checking and automated correction suggestions for Japanese technical documents using textlint's linting capabilities.

Enables AI assistants to convert text to high-quality speech audio using MeloTTS. Automatically splits long texts into segments, generates WAV files, and merges them using ffmpeg with support for multiple languages and customizable speech parameters.

Local Korean text-to-speech MCP server using a fine-tuned CosyVoice2 model, enabling voice synthesis directly from Claude or Codex with privacy and no API costs.

Enables agents to convert text to speech using OpenAI's TTS models with voice selection, delivery instructions, and queue-based audio playback. Supports both blocking and non-blocking modes for flexible audio generation and playback control.

Enables MCP clients to speak by running local voice models using Chatterbox Turbo TTS or Kokoro TTS, with support for voice cloning, paralinguistic tags, and multiple voices.

Enables MCP clients to speak text aloud on macOS using the built-in say command, with no external speech API or keys, and to list available voices and control rate or voice selection. Requests from multiple client threads share a single FIFO playback worker, so speech plays one item at a time and can be inspected, stopped, or muted in hold or discard mode.

Enables Claude Code and Codex to play spoken alerts on a Mac when a task finishes or user attention is needed, using built-in or custom voice lines while staying quiet during keyboard use, calls, Focus modes, or configured locations.

Enables AI agents to ring or text a user's actual iPhone, read a question or update aloud, and return the spoken answer back to the agent as text. Calls and messages land in a single titled thread per agent, with tools for polling results, waiting for replies, and labeling conversations.

Hosted text-to-speech MCP server for AI agents with 54 neural voices in 9 languages, including Brazilian Portuguese. Pay-per-use API, no GPU or subscriptions needed.

Creates short videos for TikTok, Instagram Reels, and YouTube Shorts using the Model Context Protocol (MCP) and a REST API.

Enables coding agents to hold spoken conversations by exposing speech-to-text and text-to-speech tools over MCP, routing them to a local daemon that drives a Chrome window using on-device speech recognition and Piper synthesis. It supports listening, speaking, and reading files aloud within a Claude Code plugin or an MCP gateway.

Enables AI agents to access local voice synthesis, zero-shot cloning, and voice catalog tools through native MCP tool calls for applications like Claude and Cursor.

A Model Context Protocol server that wraps Volcengine's Text-to-Speech API, allowing users to generate speech from text using natural language parameters for customizing voice type, emotion, and speed.

Adds text-to-speech capabilities to Cursor IDE, allowing your AI assistant to speak responses, summaries, and explanations out loud using OpenAI or ElevenLabs.

An MCP server for AI voice synthesis with an inline audio player, allowing users to give their AI assistant a custom cloned voice using DashScope or ElevenLabs.

A stdio MCP server that lets AI coding tools on a Mac speak text aloud through the local Speaklna text-to-speech app. It exposes four tools (speak, stop, status, voices) so agents can voice replies, halt playback, check state, and list available voices, but cannot import voices or change settings.

Enables AI agents and applications to send audio notifications with text-to-speech, message streaming, agent-to-agent conversations, and web push notifications through a persistent message store and MCP integration.

Enables bidirectional voice interaction for Claude Code using local speech-to-text and text-to-speech models optimized for Apple Silicon. It provides tools to listen to user speech via microphone and speak responses aloud through system speakers.