"A server for enabling an AI agent to view and analyze video files" matching MCP servers:

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

MCP server that provides a local Web production console and HTTP control plane for AI video creation, exposing tools for project/revision management, media analysis, editing, review, and delivery while keeping formal rendering behind explicit approval gates.

An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Renders JavaScript-heavy pages in a real headless browser so agents can read the content that actually loads, returned as clean markdown, text, or HTML. Also exposes screenshots, page links, and the XHR/fetch calls a page makes, with sign-in sessions, selector scoping, and clear labels for bot checks, login walls, or empty renders.

Enables AI agents to produce professional promo videos by providing tools for capture, media search, scene writing, rendering, editing, and incremental revision.

Enables MCP clients to run project-scoped video editing workflows: propose and approve editing strategies, apply validated plans, review immutable versions, and export final renders via FFmpeg, with durable persistence and approval gates.

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

Dynamic QR code platform for AI agents. Create, customize, and track QR codes without regenerating images. 37 tools covering 11 QR types (URL, vCard, WiFi, event…).

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.

An MCP server for rendering common ECharts visualizations from structured tool arguments, exposing per-chart opener tools that map to independent HTML app resources.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Publishes a spending-summary tool alongside an interactive HTML view, letting people click a category in the answer to fetch the individual expense records behind that total. Keeps calculations and their supporting evidence together in a single inspectable flow.

Stdio MCP server for sandboxed file access — read files, search content, safely edit with checksums, and manage file structure.

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 like Claude to interact with Figma designs through 50+ tools for creating, styling, and manipulating design elements, components, and variables via a WebSocket relay and Figma plugin.

It enables AI agents to call a small set of reliable, permission-aware tools generated from an existing website through the Model Context Protocol, without rebuilding the site.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

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

Enables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.

An MCP server for programmatic video editing using ffmpeg, enabling draft creation and refinement via natural language.

Enables read-only listing and reading of files in an Azure Files SMB share, enforcing each user's NTFS permissions per request.

An MCP server that generates MP4 b-roll videos from scene specs, enabling AI agents to create branded overlays for short-form video without After Effects.

MCP server for video analysis — extracts transcripts, key frames with OCR, and annotated timelines from video URLs. Supports Loom and direct video files (.mp4, .webm). Zero auth required.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

MCP server for evidence-aware video research, providing tools to analyze local videos, inspect specific time windows, and analyze Bilibili videos with provenance tracking and optional audio removal for privacy.

Enables extracting screenshots from video files at specific timestamps or intervals. Supports multiple video formats and output customization including resolution, quality, and format options.

A Model Context Protocol server that provides video manipulation capabilities, allowing users to clip, merge, and split video files through MCP integration.