"A guide to creating a presentation" matching MCP servers:

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

Enables MCP-capable chat clients to synthesize speech from text, convert it with a local RVC voice model, and render the result in an inline audio player.

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 conversion of YouTube videos to MP3 format through the Youtube To Mp315 API. Supports checking conversion status, retrieving video titles, and asynchronous video-to-audio conversion with customizable quality and time range settings.

Enables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.

An MCP server that provides speech-to-text transcription and speaker diarization using OpenAI Whisper and pyannote.audio.

A server that generates MP3 audio files from text using Kokoro TTS technology with optional S3 upload capabilities.

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.

An MCP server that enables voice-to-voice AI conversations using ElevenLabs for speech synthesis and recognition, with tools for voice management, text-to-speech, and speech-to-text.

Enables MCP clients such as Claude to generate spoken audio locally, narrating English with Kokoro and Malayalam with IndicF5, Parler-TTS, Piper or MMS, including cloned Malayalam voices, pronunciation lexicons, and number/currency expansion. Outputs loudness-normalised WAV or MP3 and runs long narrations through a pollable job queue so tool calls never time out.

Enables submitting audio via URL or Base64 for local Whisper transcription, then checking job status and results or deleting transcription jobs. It provides asynchronous job handling and SSRF-protected downloads/callbacks without cloud API calls.

Lets AI assistants render HTML animations to MP4 or GIF in 16:9, 9:16 and 1:1, preview single frames to check their own work, and finish videos with royalty-free music, AI voiceover, burned-in captions, titles and logos. It renders code frame by frame in a real browser rather than generating video from a text prompt.

A local MCP server that rings a bell through your speakers to provide audible notifications when AI completes tasks or needs attention.

Enables reading and creating projects in a local CapCut draft library through natural language — listing timelines, checking for missing media, and generating new edits from clips, with cuts automatically matched to the beat of a track. It works by cloning an existing draft as a structural template, so new projects inherit CapCut's undocumented file format.

Enables Claude to turn a described beat into a loopclub deep link for auditioning and renting on-chain by encoding track specs into a ?jam= URL and returning an ASCII grid. It also supplies vocabulary, genre examples, and a jam prompt to help generate idiomatic loops.

Enables AI models to read and edit your own BandLab songs via natural-language prompts, performing concrete mix operations like adjusting track levels, pan, effects, and arrangement while creating new non-destructive revisions.

Enables AI assistants to generate and control real-time audio synthesis through natural language descriptions using SuperCollider. Features 10 built-in synth types, pattern sequencing, audio recording, and server lifecycle management for creating sounds from simple English descriptions.

Enables MCP-compatible agents to split a finished song into vocals, drums, bass, and other stems using local Demucs or a remote command, with asynchronous job status and cancellation.

Enables creating, inspecting, validating, and rendering NES FamiStudio .fms projects from plain JSON without a GUI.

Locally converts a known BPM into per-beat, eighth-note, sixteenth-note, and bar durations, compares two reported tempos to flag possible half/double-time interpretations, and lists nearby Camelot codes for a key estimate. Runs over stdio with no audio, account, or network access required.

Lets AI tools compose music live in the Bosca Ceoil Blue app, creating and editing songs, instruments, patterns and arrangements with playback control and undo, then exporting to WAV, MIDI, XM or MML.

Enables MCP clients to play a fixed built-in audio track and display native Windows/macOS desktop notifications through stdio.

Enables AI agents to list consent-approved cloned voices, render speech into watermarked audio files with quality scores, poll long-running jobs, verify outputs, and guide humans through consent steps, all locally without cloud services.

MCP server that connects AI assistants to FMOD Studio via its scripting terminal, enabling live game-audio authoring such as creating events, importing sounds, routing mixers, and building banks through natural language.

Enables audio file analysis using Google's Gemini multimodal models with support for additional context and system instructions to guide the model's behavior.

Enables AI assistants to control MIDI devices and synthesizers through WebMidi.js integration. Provides tools for sending notes, control changes, creating virtual ports, and executing complex musical sequences.

Enables Claude or any AI agent to operate Live 12 Intro end to end: creating tracks and scenes, writing and quantizing MIDI clips, loading audio onto the Arrangement timeline, setting device parameters in real units, drawing clip automation, mixing with real sidechain, and rendering or analyzing audio so the agent can check its own work. It exposes 57 tools over MCP or a local JSON socket, working within the stock Intro edition's 16-track, 16-scene limits.

Provides audio feedback by playing sound effects when Cursor AI completes code generation, creating a more interactive coding experience.

A Model Context Protocol server that enables fast and free lipsync video creation for a wide range of digital avatars, supporting both audio and text inputs to generate synchronized lip movements.

Local speech recognition MCP server powered by FunASR and SenseVoice. It provides privacy-friendly audio transcription through a transcribe_audio tool.

Enables AI assistants to generate complete Yukkuri-style commentary MP4 videos from a script, including synthesized speech, subtitles, illustrations, photos, BGM, and sound effects.

Enables AI video dubbing from any MCP-capable agent: upload a video or provide a URL, submit a dubbing job, poll progress, and download the finished MP4.

A self-contained daemon that watches a directory, transcribes anything that lands in it, and presents the results to any AI agent through a standard protocol — no cloud, no subscriptions, no vendor lock-in.

A voice-to-text transcription service that converts audio files to transcripts using SiliconFlow, supporting both multipart/form-data and base64 formats.

Enables recording audio from a microphone and transcribing it using OpenAI's Whisper model. Works as both a standalone MCP server and a Goose AI agent extension.

MCP server that transcribes local media files and URLs via Deepgram, writing Markdown transcripts to disk with strict per-job cost ceilings and caching. It also provides a CLI and optional transcript formatting through a language model.

A local stdio MCP server that lets an Agent use configured multimodal providers to inspect images, video, audio, and music files, acting as a sensory layer for text-only LLMs.

An MCP server to control Ableton Live via the Live API, offering curated tools for transport, tracks, clips, devices, automation, and more, plus a generic layer to access the entire Live Object Model.

A Model Context Protocol server that enables AI assistants like Claude to generate lyrics, songs, and background music through Mureka's APIs.

MCP server that enables AI agents to watch and analyze videos from 1800+ sources, with persistent indexing, OCR, transcription, and a self-verification loop for debugging.