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

Enables inspection and editing of Cascadeur rigs, controller animation, poses, keyframes, motion plans, review images, and FBX exchange through 49 structured tools plus optional Python execution.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Enables AI assistants to inspect and organize Adobe Premiere Pro projects, edit timelines with frame-accurate cuts and trims, animate motion and opacity keyframes, and trigger exports through natural language.

Enables AI assistants to programmatically inspect projects, create compositions and layers, apply effects, animate properties, and manage render jobs in Adobe After Effects through natural language.

Enables WorkBuddy and other MCP-compatible clients to generate images and videos from natural-language prompts through Agnes AI, returning online URLs and locally saved files.

Windows-optimized MCP server that enables control of Blender 4.0+ through 21+ tools for scene management, object manipulation, and asset downloads from PolyHaven, Sketchfab, Hyper3D, and Hunyuan3D.

MCP server for Takes, a free, open-source Mac teleprompter and recorder for talking-head videos. It lets an AI assistant write scripts and storyboards, manage takes, make edits and draft the posts for LinkedIn, X, YouTube and Shorts.

Enables MCP clients to operate local Adobe Premiere Pro projects, covering media ingest, bins, sequence and timeline editing, transitions, effects, keyframes, captions, markers, metadata, proxies, multicam, color, audio, and exports through 283 discoverable tools, 13 context resources, and 10 guided prompts. A bundled CEP panel provides the supported production bridge, with read-only connection verification and higher-level workflows for assembling product spots and motion-graphics demos.

Enables AI clients to drive local video editing projects through a CEP bridge, covering media ingest, sequence and timeline editing, effects, keyframes, captions, markers, audio, color, and exports across hundreds of discoverable tools. Ships context resources, guided prompts, and higher-level assembly workflows for agent-driven editing.

A local MCP server that bridges Logic Pro MIDI data via an AUv3 plugin, enabling reading, creating, and manipulating MIDI regions and tracks through tools like read_logic_track and create_midi_region.

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.

Enables Claude to inspect and build compositions in an open Adobe After Effects project, animate layers and effects, preview real frames, compare against reference video side by side, measure and recreate camera moves, detect cuts and beats, and render MP4s.

Renders validated declarative scene specifications into MP4 videos inside disposable, network-disabled containers, then serves an embedded player with playback controls and diagnostics through MCP Apps. Users can iteratively revise scenes conversationally, with revision history preserved and identical renders reused per account.

Enables Claude Code to use Alibaba Cloud Token Plan models via a local proxy that maps Anthropic-style model names to Alibaba IDs and provides missing endpoints like model discovery.

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.

Converts a single-file MP3/M4A audiobook plus its EPUB into a chaptered M4B, using silence-gap detection to find real chapter boundaries, with checkpointed job-based progress, EPUB preview, boundary inspection/waveform review, metadata lookup, and cover fetching/embedding tools for resumable, verifiable audiobook production.

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 reading and controlling a Universal Audio Apollo interface: channel names, faders, preamp gain, cue sends, monitor control, and more via the UA Mixer Engine's local TCP API.

A Model Context Protocol server that enables fetching and processing images from URLs, local file paths, and numpy arrays, returning them as base64-encoded strings with proper MIME types.

An MCP server that parses Douyin share links and performs intelligent content analysis using the Doubao video understanding model. It provides structured outputs including video summaries, categorized outlines, and step-by-step tutorial information.

MCP server for GIF animation analysis. Provides metadata extraction, individual frame export, and per-frame timing information.

An MCP server that extracts rich metadata (title, description, duration, chapters, subtitles, statistics, etc.) from media URLs across thousands of sites using yt-dlp, and also provides transcript fetching and search capabilities.

Record any browser page as GIF or video via MCP — powered by Playwright + ffmpeg

Enables fetching, searching, and analyzing YouTube video transcripts in multiple languages using yt-dlp. Supports timestamp filtering, language detection, and transcript summaries with robust error handling for production use.

Enables fetching YouTube video transcripts with metadata, including timed captions in multiple formats (JSON, SRT, VTT, CSV, TXT) and preprocessing options.

A Model Context Protocol server that enables retrieval of transcripts from YouTube videos. This server provides direct access to video transcripts and subtitles through a simple interface, making it ideal for content analysis and processing.

Enables AI agents to automate a browser-based kinetic typography and video editing interface, including loading lyrics, choosing styles, setting BPM, clicking controls, capturing previews, and exporting MP4 or transparent PNG sequences.

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.