"Asynchronous command execution for OpenCode terminal tasks" matching MCP servers:

Enables voice input for AI coding assistants by recording audio, transcribing it locally with Whisper, and optionally typing the text at the cursor position. Supports multiple languages and works with MCP-compatible tools like OpenCode, Claude Code, and Cursor.

Enables transcription of videos and audio from 1000+ platforms (YouTube, Bilibili, TikTok, etc.) using subtitle extraction first, then local Whisper transcription, with support for long videos, async tasks, and Chinese ASR optimization.

Enables MCP clients such as Claude Code, Codex and Cursor to retrieve timestamped transcripts of public YouTube videos, either from cache, from native captions, or via asynchronous audio-generation jobs that are polled by job ID. It returns the source URL, selected language and millisecond-offset segments without summarizing the video itself.

Local speech-to-text transcription using Microsoft's VibeVoice-ASR model with speaker diarization, enabling audio transcription directly in AI tools like Claude Code, Cursor, and OpenCode.

Enables Claude Code to leverage Chinese LLMs for multimodal tasks including image analysis, audio transcription, and deep synthesis via MCP protocol.

Fast MCP Telegram — Production-grade Telegram MCP server with direct MTProto API, multi-user ACL, dual transport (stdio + HTTP SSE), voice transcription, and context-optimized design. One-command setup with uvx fast-mcp-telegram

Enables an AI assistant to have its recent code actions summarized aloud through system speakers, using offline native voices or cloud neural voices. It supports asynchronous playback and voice listing so users can hear what the agent did without reading the full response.

This MCP server enables Claude to speak summaries, announcements, and explanations aloud using text-to-speech — right from your terminal.

An MCP server that lets AI assistants send spoken audio notifications using high-quality AI voices, so you don't have to stare at the screen waiting for long tasks to finish.

Enables MCP clients to submit completed speech or typed text to a self-hosted decision engine and receive judgments such as ordinary speech, command, retained thought, uncertainty, or no action, along with session and decision inspection.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

MCP server for text-to-speech using macOS say command, enabling speech synthesis, audio file generation, and voice management.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

An 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.

Provides voice notifications using Grok's text-to-speech API to alert users when Claude Code completes tasks, with support for both local and remote server configurations.

Connects Claude Desktop to Hugging Face Spaces with minimal setup, enabling capabilities like image generation, vision tasks, text-to-speech, and chat with AI models.

Enables supported local AI clients to control a visible desktop presence through bounded presentation tools such as animations, window control, and short local speech over a loopback endpoint, without granting decision or execution authority.

Read-only MCP server for Telegram that enables reading messages and transcribing voice, audio, and video notes via the Telegram API for use with Codex and Claude Code.

Screen-aware voice command layer for AI agents that captures screen context and instructions to build agent-ready commands for various tools.

Transcribe any video URL to text with one command, supporting 1000+ sites via yt-dlp and multiple ASR providers.