"Interface Documentation for Fetching Page Information" matching MCP servers:

A local stdio MCP server that enables validated access to official ElevenLabs APIs with cost controls, local media storage, and audio export for Godot.

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.

Voice interface for Claude Code: you talk, the agent listens, codes, and talks back while it works. Live speech-to-text with turn-taking, Grok/xAI voices with per-subagent personas, and a real-time HUD dashboard.

Enables agents to inspect local videos, audio recordings, and documents by producing storyboard grids, timestamped transcripts, page images, and page-aligned text, with tools for probing media, zooming into details, locating terms, and reading subtitles. It works only with local absolute paths and does not download content or call an LLM.

Multi-provider AI video, speech, music, and transcription MCP server enabling video generation, image-to-video, TTS, music creation, and speech-to-text via a unified interface.

Analyze an hour-long YouTube video sentence by sentence in three minutes, and extract the information you need from the screen. Open-source local MCP server for AI clients.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

Wraps the Transkriptor developer API to transcribe audio, video, public URLs, and live meetings, with support for fetching transcriptions, summaries, exports, file management, custom vocabulary, webhooks, text-to-speech, and AI chat knowledgebases.

An MCP server that enables LLMs to access the NijiVoice API for text-to-speech generation, supporting features like fetching available voice actors and checking credit balance.

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

Enables real-time voice agents and streaming audio pipelines to detect conversational turn completion, distinguishing finished speech turns from mid-sentence hesitation pauses using acoustic VAD and semantic scoring. It provides low-latency decision and telemetry output through a native MCP interface for integration with MCP-compliant clients.

A Model Context Protocol server that enables AI assistants to utilize AivisSpeech Engine's high-quality voice synthesis capabilities through a standardized API interface.

Enables MCP clients to place real phone calls to businesses in the US and Canada, navigating phone menus, waiting on hold, asking the agent mid-call for information, and returning structured answers with transcripts. Supports booking, quotes, cancellations, and multi-business calls in parallel.

Enables autonomous agents to orchestrate HubX mobile AI tools for vision diagnostics, voice transcription, photorealistic image generation, and spatial design through a native MCP interface.

A comprehensive audio MCP server that enables AI agents to generate speech, transcribe audio, clone voices, analyze speech quality, design soundscapes, and manage audio assets through a standardized interface.

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 users to prepare and conduct phone calls for errands, gathering context before dialing and looking up missing information through connected tools during the conversation.

Enables users to manage Gmail accounts using AI agent-assisted operations via an MCP protocol, supporting email search, reading, deletion, and sending with a voice-powered interface.

Enables any LLM to watch videos by providing scene-aware keyframes, storyboards, and timestamped transcripts through tools for opening videos, fetching frames, and retrieving transcript segments.

Enables macOS control, web scraping, news fetching, and workspace automation through an MCP server.

MCP server for fetching YouTube video transcripts without an API key.

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.

Enables agents to discover devices, query their capabilities, invoke system calls, and stage resources or deliver apps to connected WishOS hardware through a self-hosted connector and relay. It routes device-initiated tasks into an existing harness session (Codex, Claude Code, and others), keeping inference, tools, and history with that agent while handling voice, interface, and app transfer to the device.

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 parsing Douyin video information, downloading videos without watermark, and transcribing speech to text using Tencent Cloud ASR.

Enables Claude to fetch YouTube video transcripts, using existing subtitles first and falling back to OpenAI Whisper transcription of the audio, with optional saving as Markdown files into a vault folder. It can run locally over stdio, be reached via an authenticated HTTP endpoint, or be exposed to claude.ai as a cloud connector backed by a local worker that does the actual fetching.

Enables hands-busy small online sellers to use voice-driven MCP tools for deterministic margin and listing checks and to draft ad headlines, 30-second shorts scripts, and detail page outlines.

Voice interface for Claude Code enabling hands-free, conversational interaction entirely on-device for Apple Silicon Macs. It provides push-to-talk transcription and automatic spoken responses via local AI models.

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.