"Comparison of cloud service providers: Google Cloud, AWS, Vercel, Supabase" matching MCP servers:

Provides translation and language detection tools to AI agents, processing text, audio, and Google Meet recordings with emotional voice style preservation via Google's Gemini Live API.

Enables control of Spotify playback, music search, and playlist management through natural language commands. Available in both Python and Vercel implementations with comprehensive OAuth2 authentication and device management.

Enables Alexa+ voice intents to be evaluated and orchestrated through AWS Bedrock Claude 3.5 Sonnet, coordinating multi-surface actions across Ring, Fire TV, and Wearable AI devices via MCP tools, prompts, and resources.

Provides voice recognition and text extraction capabilities with support for both stdio and MCP modes, processing audio files or base64 encoded data and returning structured results with language, emotion, and speaker information.

Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.

Provides on-device Chinese speech recognition with traditional Chinese (Taiwan) output via MCP server, HTTP API, and CLI, ensuring privacy by processing audio locally without uploading to cloud services.

Enables AI clients to watch local video files or YouTube/Bilibili and other supported URLs, receiving timestamped transcripts, subtitles, searchable text and keyframe contact sheets. Runs fully offline with local speech recognition and bundled ffmpeg, so no API key or cloud upload is needed.

Enables local text-to-speech synthesis for Claude and Cursor using Supertonic 3, with support for multiple voices, expressions, and languages. No API key or cloud required.

SeaMeet MCP connects Claude, Cursor, Codex, and other AI agents to SeaMeet meeting recordings, transcripts, AI summaries, screenshots, action items, webhooks, and desktop recording controls. Use it to search meeting memory, read synced cloud recordings, and automate meeting notes through the Model Context Protocol.

An MCP server that enables transcribing local audio files and Telegram voice messages using OpenAI's Whisper via local inference or cloud API. It supports multiple audio formats, automatic language detection, and optional word-level timestamps for AI-powered audio analysis.

Enables AI agents to interact with the ParrotScribe transcription service on macOS, providing tools to start/stop transcription, retrieve real-time and historical transcripts, and search across sessions.

A Windows-native MCP server that lets Claude Desktop transcribe audio files locally using whisper.cpp, with no internet connection required.

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

Enables AI assistants to transcribe links (YouTube, Google Drive, Dropbox), list and search your recordings for spoken words and moments, and read transcripts in json/txt/srt/vtt, summaries and metadata. It also lets them request new summaries and delete recordings, all through your own account with API-key or OAuth sign-in.

Enables transcription, summarization, and action item extraction from audio files on your Mac using MacWhisper and Claude Desktop, all locally without any cloud APIs.

Pay the provider's own price. No markup, no subscription. Use 400+ Vercel AI Gateway models, including Veo, Kling, Seedance, Nano Banana and GPT Image, to make video, images, voice and text right inside Claude, ChatGPT or any MCP app. Deploy your own copy to Vercel in one click; every call is billed to your own Gateway credits.

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.

Lets AI assistants query available voices from an OpenAI-compatible TTS service and synthesize text into audio with a chosen voice, tone, and speed, returning a public audio URL instead of Base64 data.

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 MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.

Automatically transcribes Google Chat voice messages using Groq Whisper API, and also supports local audio file transcription.

Provides local vision and audio perception for MCP-compatible agents, enabling them to read images, transcribe text from visual media, analyze videos, and convert speech to text entirely on-device. It is privacy-focused with no cloud upload or API keys by default, using Ollama for inference.

Enables AI agents to send the same short audio clip to multiple speech-to-text providers and compare transcripts, CER/WER, latency, and estimated cost. It also lets agents check which providers are configured and estimate costs from a built-in price table.

Local-first CLI + MCP server for meeting recordings - Whisper transcription,

Enables AI apps to transcribe local audio and video files on the user's own GPU, producing SRT/VTT subtitles and text without cloud uploads. It also helps find media files, list available devices, and list supported languages and models.

Enables transcription of video speech and burning TikTok/Reels-style animated captions into MP4 files locally, using 15 preset styles with batch folder jobs and optional cloud transcription, correction, translation, and emoji features.

Enables local, upload-free analysis of publicly viewable videos through tools that pull metadata, chapter plans, platform subtitles or speech-to-text transcripts, sampled frames and contact sheets, 527-class sound event tags, and comment analysis. It downloads only the minimum necessary bytes, so users can inspect long videos section by section, job-poll lengthy runs, and check the local model/environment setup without sending media to any cloud service.

Provides multimedia understanding tools for LLM agents, enabling image, video, audio analysis and speech transcription via cloud-based MiMo V2.5 through OpenAI-compatible endpoints.

Local Windows x64 MCP server for USB HID mouse control and optional voice dictation. Requires compatible uMouse hardware, firmware and x64 Node.js 22+. MCPB 0.1.1 packages the legacy 0.1.0 stdio runtime; shared-v2 is a separate source development path. The MCPB includes no cloud credentials, defaults speech recognition to disabled, and supports optional local Windows Speech.

Enables transcription of YouTube videos by using available captions or falling back to actual audio with local Whisper ASR and multiple free providers. It supports job status, transcript retrieval and search, audio excerpts, and export formats while keeping source links and timestamps.