"영상 (videos/images)" matching MCP servers:

Your agent seeks what search can't find. A self-hosted perception MCP server that transcribes speech, reads behind logins, sees images and video frames, crosses languages, and remembers.

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.

Enables transcription of videos and audio from 1000+ platforms (YouTube, Bilibili, TikTok, etc.) using subtitle extraction first, then local Whisper transcription, with support for long videos, async tasks, and Chinese ASR optimization.

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.

Enables AI agents to analyze videos by producing timestamped transcripts, keyframe contact sheets, and metadata reports from local files or online URLs, fully offline and without API keys.

Enables AI assistants in MCP clients to turn long videos from YouTube, VK Video, RuTube, Dzen, Twitch, Yandex Disk, Google Drive or direct links into captioned vertical Shorts/Reels, transcripts and articles, returning links to the finished clips. It also exposes read-only modes and job quoting so clients can inspect sources and estimate credit usage before creating anything.

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

Translate PDF, Word (DOCX), Excel (XLSX) and PowerPoint (PPTX) files, images, subtitles and text. Turn audio and video into transcripts or translated subtitles. Preserve layout where supported. Requires an Equalang API key and credits.

An MCP server that enables AI agents to analyze videos locally by extracting transcripts, detecting scene changes, and returning key frames.

✨ 为你的 AI 助手装上 B 站的眼睛：一键提取视频字幕与热门评论，助力高效信息总结 🚀 ✨ Equip your AI assistant with "Bilibili Eyes": One-click extraction of video subtitles and popular comments for efficient information summarization 🚀

MCP server for vdl that lets AI assistants resolve, download, and transcribe videos through a self-hosted vdl instance.

Enables AI assistants to generate animated overlays and edit short videos — cutting clips together, removing pauses, adding captions, and exporting overlays as MP4, MOV or WebM with transparent or green-screen backgrounds. All rendering, transcription and media handling happen locally on the user's own computer.

MCP server for recognizing and generating images, videos, and audio via DashScope, with support for large video uploads and local output previews.

Enables MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.

An MCP server that turns AI agents into product presenters, enabling them to record keynote-quality demo videos by controlling screen recording, mouse, Chrome, and narration.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Enables AI assistants to transcribe Instagram, TikTok, YouTube, and Facebook videos, extract comments, and manage transcription jobs and credit balances through ReelScribe.

Provides local vision and audio perception for MCP-compatible agents, enabling them to read images, transcribe text from visual media, analyze videos, and convert speech to text entirely on-device. It is privacy-focused with no cloud upload or API keys by default, using Ollama for inference.

Enables AI agents to research Bilibili and YouTube videos through language, visual, or multimodal analysis, returning structured evidence with source-time ranges, availability states, and explicit analysis limits. Supports caption or audio-based transcription, sampled comments, and quality-controlled media windows.

Converts screen-recorded walkthrough videos into timestamped transcripts, extracted frames, scene-change anchors, and interleaved slices that pair each frame with the speech following it, so a coding assistant can read video feedback. All processing runs locally via ffmpeg and Whisper, with results cached to disk and exportable as transcript, frame images, and a README skeleton.

Enables AI coding agents to access Bilibili video data and turn videos into notes, including search, video info, subtitles, chapters, audio download, ASR transcription, comments, uploader collections, and favorites.

Enables Claude to fetch the spoken text of YouTube videos from any URL or video ID, listing available captions and languages and paging through long transcripts. It also handles proxy configuration to work around YouTube IP blocks.

Transcribes videos from 1000+ platforms (YouTube, TikTok, Vimeo, etc.) and local video files using OpenAI's Whisper model, with support for 90+ languages and multiple output formats.

Enables local, upload-free analysis of publicly viewable videos through tools that pull metadata, chapter plans, platform subtitles or speech-to-text transcripts, sampled frames and contact sheets, 527-class sound event tags, and comment analysis. It downloads only the minimum necessary bytes, so users can inspect long videos section by section, job-poll lengthy runs, and check the local model/environment setup without sending media to any cloud service.

Extracts transcripts or spoken captions from multi-platform video links (Bilibili, YouTube, Douyin) and returns concise Markdown summaries or full transcripts, saving tokens by keeping full text out of the conversation.

Enables agents on Windows to inspect video and audio evidence by returning adaptively selected frames, subtitles or optional local ASR transcriptions, timestamps, and processing status from local files or supported URLs.

Enables transcription of YouTube videos by using available captions or falling back to actual audio with local Whisper ASR and multiple free providers. It supports job status, transcript retrieval and search, audio excerpts, and export formats while keeping source links and timestamps.

Enables users to extract transcripts from Douyin videos, parse video metadata, retrieve download links, and transcribe audio files, using HTTP parsing with Chrome/Edge fallback and SiliconFlow cloud ASR by default.

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.

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