"Methods for Finding People on the Internet" matching MCP servers:

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

Enables AI assistants to download YouTube videos and transcribe them locally using OpenAI's Whisper speech recognition model.

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 self-hosted MCP server that connects AI clients to local media-generation backends like ComfyUI and Blender, and provides built-in utilities for video/audio analysis, editing, subtitles, speech, and scene detection via a persistent file cache.

Enables Alexa+ to run spoken mock technical interviews by parsing a candidate's resume and target job description, generating tailored questions, and scoring each answer against Bar Raiser rubrics via Amazon Bedrock. It also produces a session report with score breakdowns, weak topics, and a concrete practice plan.

Enables AI clients to watch and hear videos from local files or YouTube, Vimeo, and Loom links by returning timestamped key frames, a transcript, a contact sheet, and a combined timeline, with all processing done locally.

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.

Enables spoken conversations with Claude on a Mac: Claude speaks through speakers, listens to the user's natural replies, and transcribes them locally. No audio leaves the computer, and it includes tools for voice setup and a hands-free voice mode.

MCP server for local speech-to-text using Whisper Large V3 (MLX), enabling audio transcription with text/timestamps/SRT output and LLM-based correction, all running offline on Apple Silicon.

Voice input for Claude Code — speak Vietnamese or English; hold a hotkey, speak, release, and the transcribed text is cleaned and pasted into the input box for editing before sending.

Enables AI agents to generate spoken audio locally on a GPU via the Chatterbox models, with zero-shot voice cloning from reference clips, multilingual output, and sentence-aligned chunking for long text.

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.

Make phone calls and join Zoom, Microsoft Teams and Google Meet meetings from any AI agent. A self-hosted, open-source voice agent that calls businesses and people through your own SignalWire or Twilio number, joins meetings as a bot that answers when spoken to, says it is an AI, and returns the outcome, decisions, action items and transcript.

Enables agents to submit audio files to the local Meeting Transcriber macOS app, retrieve diarized transcripts, assign speaker names, and start or stop automatic meeting detection over its localhost automation API. Everything runs on-device, so no audio or transcripts leave the Mac.

Provides programmatic access to Apple Voice Memos on macOS, enabling AI assistants to list, retrieve details, get audio, and transcribe recordings.

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 such as Grok Bot to create and join GifOS meetings, send in a visible note-taking bot that transcribes participants locally via Whisper, post chat content, and read back or save the transcript. Everything, including the browser, bot credentials, and transcripts, runs on the user's own machine with no GifOS account or API key.

Enables AI to analyze audio files for loudness, voice quality, and more via the AudioLab API, supporting both public URLs and local files.

Enables high-quality transcription and subtitle generation from local media files or URLs using Faster Whisper on local hardware. It supports automatic language detection and integration with MCP clients for seamless speech-to-text workflows.

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.