"Open source MCP (Model Context Protocol) implementations" matching MCP servers:

Give your AI assistant eyes and ears — analyze any video, audio, or image, entirely on your machine.

Enables Alexa+ to retain and recall a lightweight per-user context thread across separate voice interactions, supporting starting, querying, and listing active contexts for continuity.

Enables AI assistants to summarize, take notes on, and answer questions about YouTube, Bilibili, and Xiaohongshu videos by providing subtitles and local speech transcription with timestamps via MCP.

Enables secure, self-hosted audio transcription through a single MCP interface, letting users route recordings from authorized sources to Microsoft MAI, ElevenLabs Scribe, or Groq Whisper and receive a consistent transcript schema.

Local MCP server for private, consent-based speaker identification and attribution, with per-language voiceprints and calibrated match thresholds. It lets AI assistants know who is speaking in a room or transcript without cloud services.

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.

MCP server for audio transcription using OpenRouter models, supporting verbatim, cleaned, and custom transcription modes.

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

MCP server that provides a transcribe_audio tool to convert voice messages from channels into text using OpenAI Whisper, enabling Claude Code to process audio attachments.

An MCP server that makes AI agents speak a brief summary of every response out loud using TTS.

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.

Enables MCP clients such as Claude Code, Codex and Cursor to retrieve timestamped transcripts of public YouTube videos, either from cache, from native captions, or via asynchronous audio-generation jobs that are polled by job ID. It returns the source URL, selected language and millisecond-offset segments without summarizing the video itself.

MCP server for SpeechWeave transcription, enabling AI assistants to transcribe local files and URLs via wait-first or async tools.

Provides AI tools with transcripts of any YouTube video, including videos without captions via AI speech-to-text, with language selection and length capping.

High-quality speech-to-text transcription using Zhipu AutoGLM ASR, supporting long audio chunking, context-aware modes, and timestamp segmentation.

Integrates OpenAI APIs into MCP-compatible clients, providing tools for text generation, chat completions, model discovery, image creation/editing, audio transcription, speech synthesis, embeddings, and content moderation.

Official Model Context Protocol (MCP) Server for QuickerSpot — AI-powered commercial radio and retail sound automation. Connect your AI Assistants (Cursor IDE, Claude Desktop, Antigravity, Hermes Agent, OpenClaw) directly to QuickerSpot's ElevenLabs V3 voice engine, AI script generator, and indoor radio mixer.

Enables AI models to speak and sing using retro-style formant speech synthesis, converting text or phoneme strings to WAV audio via MCP tools.

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.

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.