"NestJS Framework for Building Backend Applications" matching MCP servers:

Enables AI agents to synthesize and play short summaries aloud while keeping full answers on screen, with queued speech and stop control using online natural voices or offline synthesis.

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.

Enables converting video and audio files into transcripts and Traditional Chinese subtitles using Groq Whisper with a pluggable translation backend, including an English-to-Chinese pipeline and a Chinese-to-Taiwanese-Mandarin proofreading pipeline. Transcriptions run as background jobs whose progress, output subtitle paths, and setup status can be queried through the conversation.

Transcribe YouTube videos for LLM chat applications. Supports fetching transcripts in multiple languages and includes an ad-removal instruction.

Provides text-to-speech capabilities through the Model Context Protocol, allowing applications to easily integrate speech synthesis with customizable voices, adjustable speech speed, and cross-platform audio playback support.

Enables agents to generate 3D talking avatars from text descriptions or photos, and to render lip-synced talking videos from text using a photo, GLB avatar, or freshly assembled avatar. It also exposes tag vocabularies, asset search, and voice listings for building those avatars.

Enables LLM applications 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 customizable voice parameters.

Enables an Alexa+ host to place and manage customer-care calls by building a case, navigating phone menus, waiting on hold, explaining the issue, guarding sensitive disclosures, handing off identity checks, recording ticket numbers and promises, and scheduling follow-ups.

Enables a voice-first study mentor that remembers each learner across sessions, teaching at their level, running spoken quizzes graded on what was actually said, and building exam-aware study plans and morning briefings with overnight preparation. It also supports read-only Google Classroom sync, web research with sources, invite-only quiz battles between homes, and parent-visible safeguards for younger students.

Enables AI agents to access local voice synthesis, zero-shot cloning, and voice catalog tools through native MCP tool calls for applications like Claude and Cursor.

Self-hosted WhatsApp management over Model Context Protocol, exposing a streamable HTTP MCP endpoint with 30 tools for session/QR pairing, messaging, media storage, and optional on-CPU voice note transcription via whisper.cpp.

Enables watching videos with an AI coding agent that transcribes, prepares concepts and visuals, and answers questions in context of the video. Provides MCP tools for transcript reading, concept mapping, artifact building, and interactive Q&A synchronized with playback.

Enables AI agents and applications to send audio notifications with text-to-speech, message streaming, agent-to-agent conversations, and web push notifications through a persistent message store and MCP integration.

Enables seamless integration with ElevenLabs Conversational AI to manage agents, tools, and knowledge base sources. It supports RAG indexing, webhook integration, and document management for building advanced voice-enabled AI agents.

Enables end-to-end testing of voice-enabled web applications by simulating a synthetic user with a virtual microphone, virtual speakers, a real browser, and a viewable display, allowing audio injection, speech capture/transcription, and browser automation.

A FastAPI backend that integrates with ElevenLabs MCP to create an AI agent capable of making outbound calls and delivering friendly, jargon-free tech news updates.

A cloud backend for a voice assistant that processes natural language commands, manages tasks, and provides speech responses. Integrates with MCP protocol and Gemini API for Vietnamese language support.

Feedback ingestion for AI agents. Record your screen and talk; your agent does the rest — files the bugs, writes the spec, builds the backlog.

Let your AI agent call your phone and talk to you — MCP servers for live, interruptible voice calls + tiered alerts, using free self-hosted pieces (pjsua2 + whisper.cpp + Linphone). No paid telephony, no extra API key.

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.