"Information about Microsoft Office Word" matching MCP servers:

MCP server providing 115 tools to control the Windy Word voice-to-text desktop app, enabling paste, hotkeys, transcription, recording, and many other operations.

Enables transcript timestamp-aligned speech filler word removal and cutlist generation for automated video editing, with zero-dependency MCP integration.

Enables MCP clients to transcribe local audio files or public audio URLs into plain text, JSON with word timestamps, or SRT/VTT subtitles, with options to save output to a file.

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.

Converts text or transcripts into MP3 audio using Microsoft Edge's free neural voices. Provides text-to-speech and voice listing tools with no API key required.

Enables controlling a Dirtywave M8 over USB by reading its screen as text, pressing buttons, playing notes, and retrieving system information through MCP tools.

Enables AI assistants to transcribe audio and video from URLs or local files with high accuracy, speaker diarization, 119 languages, and word-level timestamps, while also supporting transcription management and caption export in SRT, WebVTT, or plain text.

An MCP server for OBS Studio that subscribes to events and maintains a history, enabling queries about audio levels, source states, and past actions rather than only one-shot requests.

Lets MCP clients such as Claude list, read, search and compare transcripts of Apple Voice Memos on macOS, keeping word-level confidence marks so uncertain words stay visibly flagged. Adds speaker separation, optional local voiceprint recognition, and independent second-reader comparisons that highlight where two engines disagreed.

MCP server for the AssemblyAI API, providing tools for transcription, subtitles, speaker turns, word search, and LeMUR-based queries.

An MCP server that enables AI assistants to search, analyze, and retrieve information about audio samples from Freesound.org through their API.

A powerful MCP tool for parsing and manipulating MIDI files that allows users to read, analyze, and modify MIDI files through natural language commands, supporting operations like reading file information, modifying tracks, adding notes, and setting tempo.

An MCP server for parsing and analyzing Ableton Live .als project files offline, enabling queries about tempo, tracks, clips, and MIDI data through tools like als_summary and als_list_tracks.

Enables searching and downloading audio samples from Freesound using keywords, filters, and sound IDs. It provides detailed sound metadata including duration, license information, and preview URLs.

A Model Context Protocol server that integrates with VOICEVOX engine to provide text-to-speech synthesis and speaker information retrieval, allowing users to generate and play voice audio from text.

Enables AI agents to programmatically scaffold Remotion projects, analyze audio for beat-synced scenes, synthesize voiceovers with word-level timecodes, preview frames, and render finished videos.

Transcribes YouTube videos or audio files to Markdown, plain-text, and Word documents.

Enables AI agents to enroll and verify voice samples against known identities, providing honest confidence signals about voice authenticity.

Turns a plain-language request into a narrated vertical motion graphics video with natural voice, word-by-word synced animation, music and sound effects, rendered locally as an MP4 ready for Reels, TikTok and Shorts. Validates scripts and estimates OpenAI API cost before spending credits, and works inside MCP-capable assistants like Claude Code, Claude Desktop or Cursor.

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 an AI client to write, queue, convert, and monitor markdown podcast scripts into spoken-word audio locally using the same configured folders and environment.

Runs entirely local media tooling as an MCP plugin: it edits and inspects video, denoises/transcribes/normalizes audio, generates images, performs OCR, does offline text-to-speech, drives the user's logged-in Chrome via CDP, and reads or creates Office and PDF documents. Everything executes on the machine through ffmpeg, faster-whisper, MossFormer2, ComfyUI/FLUX, Tesseract, SAPI and Playwright, with no API costs or file uploads.

Enables transcription of audio files using Google Gemini AI and creates a searchable knowledge base, allowing users to ask natural language questions about content in meetings, podcasts, lectures, and other audio recordings.

Enables local inspection of Apple MainStage state and patch/set information, plus MIDI control such as program changes, CC, and metronome toggle via MCP.

Gives coding agents the ability to hear and reason about audio by describing sounds, matching them to text, locating key moments, detecting realness, generating timelines, and critiquing soundtracks. It also lets agents synthesize and iteratively improve their own sounds in code.

Connects AI coding agents to PreSonus StudioLive III mixers over the local network, exposing live mixer context such as channel names, mute/solo/fader state, Fat Channel compressor/EQ models, and meter activity as MCP resources and tools for reading and reasoning about live sound engineering.

Integrates with Freesound.org to enable searching, discovering, and previewing audio content such as sound effects and music loops. It provides detailed metadata and licensing information to support video editing and content creation workflows.

Enables asynchronous Microsoft Edge text-to-speech synthesis over MCP stdio, producing MP3 or OGG/Opus audio with optional SRT/WebVTT subtitles and word-timing JSON, plus Docker deployment support.

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.

Enables asking questions about image, audio, or video files using state-of-the-art multimodal models. Powered by fal.ai for advanced media analysis and understanding capabilities.