"Information or resources about video editing" matching MCP servers:

Upload, edit, and generate videos from everyone's favorite LLM and Video Jungle.

AI-powered video editing toolkit: scene splitting, subtitle generation, thumbnail planning, color grading, and aspect ratio conversion.

A Model Context Protocol (MCP) server that learns from your video editing behavior and provides intelligent assistance for film and television post-production workflows.

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Enables real-time AI editing assistance in the WordPress block editor, allowing Claude to proofread, review, edit, translate, compose, and prepare posts for publishing.

Enables users to upload, search, edit, and generate videos through Video Jungle, supporting custom URI schemes and integration with video editing tools like DaVinci Resolve.

Enables AI agents to perform exact-match, transactional multi-file edits with atomic writes, dry-run diffs, and self-correcting error diagnostics that reduce token usage.

Provides powerful video and audio editing capabilities through FFmpeg, enabling AI assistants to perform professional-grade operations including format conversion, trimming, overlays, transitions, and advanced audio processing.

Integrates with Video Jungle to allow LLMs to upload, search, edit, and generate videos from natural language commands.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

Enables Claude Desktop to analyze individual videos or folders with Gemini, returning structured ad-creative reports, and to list videos in a folder before processing.

Lets AI agents inspect local or remote videos by reading metadata, detecting shots and cuts, extracting frames as images, and checking keyframes for seeking and streaming, all via local FFmpeg without an API key.

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 analyzing a Douyin, Xiaohongshu, or Bilibili video link to generate a reusable editing blueprint with shot, caption, speech, rhythm, and visual analysis.

Enables comprehensive video file analysis including extracting metadata, stream information, bitrate calculations, and generating technical reports. Supports all FFmpeg-compatible video formats with output in JSON, text, or Markdown formats.

Enables an agent to process local video files and then read, search and inspect the results: timestamped transcripts, on-screen text and key frames as images. Everything runs locally, so an agent can answer questions like how to perform a task shown in a screencast or meeting recording.

Enables AI agents to reverse-engineer how a YouTube or local video was made by turning it into timestamped storyboard sheets, native-resolution style frames, an audio strip with cut markers, pacing metrics, and a shot-by-shot A/V script. A bundled three-pass skill then guides the model through structure, visual design, and motion analysis to produce a recreation recipe, with no API keys required.

Enables AI assistants to summarize, take notes on, and answer questions about YouTube, Bilibili, and Xiaohongshu videos by providing subtitles and local speech transcription with timestamps via MCP.

Enables generation and enhancement of videos through a unified entry point to 200+ video models (Kling, Hailuo, Seedance, Vidu, Wanxiang), covering text-to-video, image-to-video, start-end frame interpolation, reference-to-video, video upscaling, and digital-human talking-head clips. Built for short-video operations, ad placement, and drama teams that would otherwise juggle several platforms for a single clip.

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 agents to search Bilibili, read video details and comment threads, and post comments with built-in confirmation, rate limiting, and length safeguards. Also fetches Douyin video metadata on a best-effort basis and can open Douyin links in the default browser.

Enables AI agents to turn scripts into narrated videos in YouTube 16:9 or Reels 9:16 formats using HTML pages, Remotion compositions, or HyperFrames layouts, with TTS-driven timing, captions, and optional S3 uploads.

Enables AI assistants to open YouTube links or local video files, read timed transcripts, inspect relevant frames, and answer questions with moment-level citations checked against the video.

Enables AI assistants to read Bilibili, YouTube, and local videos by supplying subtitles, speech transcription, and sampled frames with timestamps, so users can ask about content, verify on-screen details, and continue with follow-up questions. Also provides a general queue and history plus a Scroll workflow that logs into a separate Bilibili account for personalized recommendations, inbox messages, forwarded videos, and authorized delivery.

Enables shell-less agents to discover available video capabilities, gather timestamped local evidence such as scenes, frames, motion and audio, and query or diff stored observations through MCP tools. Observation and sample directories act as handles, letting hosts and the CLI read the same evidence.

Enables AI assistants and MCP clients to ingest audiovisual media from local files or yt-dlp-supported URLs, producing timestamped transcripts and scene-selected keyframes with exact-frame drill-down and transcript search.

An async video generation MCP server with multi-provider support. Currently in skeleton phase with stub implementations, it will eventually enable video generation through providers like Veo 3.1, Grok Imagine Video, and Sora 2 Pro.

An MCP server that enables LLMs to analyze video content by extracting frames as base64 images and retrieving video metadata using ffmpeg.

A cinema-grade video production MCP server that enables automated website recording, editing, and AI-powered narration using ffmpeg and Playwright. It provides tools for color grading, captioning, and converting videos into social media formats through natural language commands.

MCP server enabling video analysis via scene detection, audio transcription, visual description, and stylistic fingerprinting, with tools for full pipeline execution and storyboard generation.