"Steps to Internationalize and Localize My Application with Translations" matching MCP servers:

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.

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

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

Enables AI agents to transcribe Instagram Reels into text by providing a tool that accepts a Reel URL and returns the speech transcript along with metadata such as author and duration.

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.

Enables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.

An MCP server that provides speech-to-text transcription and speaker diarization using OpenAI Whisper and pyannote.audio.

Enables text-to-speech conversion using Google Translate's TTS, supporting many languages and accents, and saving MP3 files.

An 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.

Enables text-to-speech synthesis using Coqui TTS with multiple models and languages, long-text chunking, customizable speed and speaker settings, and voice cloning from reference audio.

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.

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 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.

Enables MCP clients such as Claude to generate spoken audio locally, narrating English with Kokoro and Malayalam with IndicF5, Parler-TTS, Piper or MMS, including cloned Malayalam voices, pronunciation lexicons, and number/currency expansion. Outputs loudness-normalised WAV or MP3 and runs long narrations through a pollable job queue so tool calls never time out.

Enables submitting audio via URL or Base64 for local Whisper transcription, then checking job status and results or deleting transcription jobs. It provides asynchronous job handling and SSRF-protected downloads/callbacks without cloud API calls.

Gives AI assistants read-only access to a conference stream's live captions and translations, saved transcripts, glossary context, and audience questions, using a developer API key from the portal. It can also be used through a hosted HTTP endpoint at mcp.deafassistant.com, so clients can connect without installing anything.

Enables AI agents to list consent-approved cloned voices, render speech into watermarked audio files with quality scores, poll long-running jobs, verify outputs, and guide humans through consent steps, all locally without cloud services.

Provides read-only access to local voice-to-text transcription history from the SayAll wireless mic app on macOS. Enables MCP-compatible assistants to query and paginate past transcripts by time and app with strong privacy boundaries.

A Goose MCP extension providing voice interaction with modern audio visualization, allowing users to communicate with Goose through speech rather than text.

Enables ChatGPT on the web to generate and play spoken audio through an embedded player, exposing a speak tool that renders text with selectable styles and scenes via configurable text-to-speech providers. It routes each request across ElevenLabs, Cartesia, Azure Speech, and DashScope in a configured failover order, picking providers by language and scenario.

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.

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 AI agents to speak and listen in real-time with interruption handling, using local ML models and hot-swappable adapters.

Enables LLMs to make voice calls and send SMS messages through the Vonage API, allowing AI assistants to perform real-world telephony operations with support for speech recognition and multi-language conversations.

Enables voice assistants like Alexa+ to triage suspicious calls, texts, and links, score scam risk, monitor live speakerphone calls with interruptive warnings, verify family safe words, remember repeat-offender indicators, and open cases with remediation steps and ready-to-file incident reports. All tools return structured JSON plus short voice-friendly responses, with zero-network link inspection and multi-region helpline guidance.

Enables AI assistants to synthesize speech using a custom cloned voice through MiniMax TTS and present it in an inline audio player with waveform visualization and transcript controls.

Exposes one tool per pipeline command so an AI agent can drive the work of turning audio into a reviewable vertical video draft: importing sources, transcribing with word timings, planning beats, generating one AI image per beat, and rendering a 1080×1920 MP4 with word-synced captions. Paid steps stay gated behind script approval given from the CLI, so agents can run the loop for Reels, TikTok and YouTube Shorts without overspending.

Enables shopkeepers to manage a credit ledger by voice in Hinglish—adding udhaar, recording payments, checking balances and top defaulters, drafting WhatsApp reminders, and mapping nicknames to customers.

Enables small dairy and crop farmers in India to talk to a voice-friendly farm ledger, with every number verified rather than guessed. It is a self-hosted MCP server over Streamable HTTP, planned to run on AWS Lambda with DynamoDB and Amazon Bedrock.