"Getting Help with GitHub Actions Workflow Coding" matching MCP servers:

Enables local, offline, CPU-only transcription of video/audio into timestamped SRT subtitles with Whisper, Chinese TTS dubbing (including multi-speaker dialogue), and synthesis of a new dubbed video in a single command. Supports dubbing silent videos, translating and re-voicing foreign-language videos, and batch-adding narration to short clips within AI workflows.

Enables chat-driven audio analysis and enhancement using local Claude, including denoising, EQ, compression, and loudness normalization, with an A/B viewer for synchronized comparison.

Voice interface for Claude Code: you talk, the agent listens, codes, and talks back while it works. Live speech-to-text with turn-taking, Grok/xAI voices with per-subagent personas, and a real-time HUD dashboard.

Enables fault-tolerant German address capture for phone agents by matching speech-recognized street names against the official directory and returning confidence scores with TTS-ready follow-up prompts.

Enables hands-free voice collaboration with a coding agent: you speak requirements aloud and hear only short, plain-language progress and completion summaries while the agent edits code, runs tests, and fixes bugs in the background. It also handles continuous speech recognition with automatic turn detection, barge-in interruption, and spoken approval prompts before risky operations.

A Model Context Protocol (MCP) server that gives AI agents the ability to process audio files — transcribe speech to text, detect spoken languages, and extract audio metadata.

Enables continuous voice conversation with AI coding assistants by locally transcribing speech with Whisper and delivering utterances as text prompts.

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.

Connects to the TypeWhisper macOS app to let coding agents transcribe local files, inspect model status, search history, and manage dictionary terms and corrections.

Enables coding agents to participate in voice calls, speaking replies while continuing their work and accepting spoken input or interruptions within the same conversation. It delivers voice input into Claude Code, Codex, Cursor, or custom HTTP endpoint workflows.

Enables coding agents to build, test, and deploy production voice agents with real phone numbers directly from the editor, including live call monitoring and sandboxed development.

Enables AI coding agents and MCP clients to generate Giggy text-to-speech audio by listing voices, requesting speech generations, and polling generation status until a downloadable result URL is ready.

Enables small online store owners to run a Shopify or WooCommerce shop by voice through Alexa+, answering questions about sales and stock while executing confirmation-gated actions like shipping orders or drafting supplier messages. Destructive or large-impact writes require a spoken code and are recorded in an audit log.

Enables AI agents to narrate internal thoughts, announce tool actions, and speak final responses aloud through local cross-platform text-to-speech. It exposes dedicated audio tools over stdio JSON-RPC for MCP-compatible clients.

Enables MCP clients to place, monitor, and hang up phone calls through authenticated tools, retrieve transcripts, and exchange correlated task results with a waiting host. It supports simulated or live calling with persisted call lifecycle records, duration limits, and idempotent requests.

Local-first voice I/O for MCP clients, enabling hands-free dictation, spoken responses, and voice-based Q&A with coding agents.

Enables Claude to interact with WhatsApp: read chats, search messages, send messages with a mandatory confirmation step, and transcribe voice notes locally, all with encrypted storage and prompt-injection scrubbing.

Enables a coding agent to see and hear the host machine via webcam stills, microphone speech-to-text, and optional text-to-speech replies, all processed locally.

Serves a single set of typed, validated tool definitions to MCP clients over stdio, letting them perform real actions through one controlled executor. The same definitions power a speech-driven OpenAI tool-calling agent, so voice and MCP clients share identical, validated capabilities.

An MCP server that watches for screen recordings, transcribes spoken feedback locally, and attaches each comment to the relevant frame, enabling coding agents to see and fix the issues you mention.