"Video content analysis and understanding for large language models" matching MCP servers:

Enables users to turn GIFs, local videos, and Bilibili videos into timestamped, queryable, and verifiable frame evidence and event timelines, while passing extracted frames to the current session's model instead of calling an external vision API.

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

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables downloading real binary files from Egnyte and uploading large files with chunked support, complementing the official Egnyte MCP connector.

Provides AI agents with local Dutch spelling and word validation using OpenTaal/hunspell, plus detailed word information from woordenlijst.org. It enables checking full texts or individual words and retrieving linguistic details for Dutch writing tasks.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

A stdio-based MCP server for fast, bounded search and navigation of large code repositories using ripgrep, with tools for project-wide search, symbol lookup, file listing, and code reading.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Turns product ideas into rendered UI screen mockups and a buildable component manifest, so downstream agents can develop real screens from the generated designs.

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.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

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 clients to manage a self-hosted content hub: create, edit, publish, and update articles across multiple platforms, plus AI writing and account management.

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

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

AutomateLab Content Distribution publishes content across DEV.to, Hashnode, GitHub Discussions, Reddit and Bluesky, with browser workflows for LinkedIn, Medium and X. Tracks publishing state and adapts content per platform. Product and documentation: https://automatelab.tech/products/mcp/content-distribution-mcp/

Enables image-only models to view videos as timestamped frames and retrieve measurable video properties such as scene cuts, silences, and loudness.

Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

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.

FastMCP server for image analysis providing OCR, metadata, and EXIF extraction.

Records and scores prospective equity earnings predictions made by AI agents, allowing comparison of different agent configurations.

Maps any source asset (e.g., long video, podcast, blog) to all platform formats (TikTok, Reels, Shorts, etc.) with per-platform adaptation rules, enabling a 'film-once-cut-many' content workflow.

Enables users to look up a Douyin creator by name, public ID, or profile URL and receive the latest video link, like/comment/favorite/share counts, a full timestamped transcript with an AI-reviewed correction and change log, and a content overview. Collection, media download, and local speech transcription are orchestrated as stdio MCP tools so Codex, WorkBuddy, and other compatible clients can run creator research and scheduled checks without extra API keys.

MCP server for image analysis, providing OCR text extraction, image metadata, and EXIF/GPS data as structured JSON for downstream processing.

Enables local discovery of research topics, interviews users to uncover their unique perspective, and turns insights into content ideas and short-form Reel scripts.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.