"How to open desktop applications on Windows" matching MCP servers:

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

Enables Codex sessions to observe and control the Windows desktop through screenshot reasoning, archived-frame inspection, pixel sampling, keyboard/mouse input, and workspace-local multimodal memory.

Enables AI assistants to capture and analyze screen content across multi-monitor setups with smart image optimization. Provides screenshot capabilities and detailed monitor information for visual debugging, UI analysis, and desktop assistance.

Image generation for Claude Code, Claude Desktop and any MCP client, using your existing ChatGPT subscription. Drives the already-signed-in Codex desktop app over the Chrome DevTools Protocol - no API key, and no Codex agent quota. Supports iterative refinement through a reusable conversation. Windows only; requires the Codex desktop app.

A Model Context Protocol server that manages desktop images, providing functionality to count, list, and compress image files stored on the desktop.

Enables recognition and extraction of architectural CAD drawings (DWG) by creating tasks and retrieving structured results for frames, title blocks, and 23 building component types, including rooms, doors, windows, stairs, and text.

An MCP server for controlling Adobe Photoshop from AI assistants, with Windows-first workflow, structured state, smoke-tested action playback, and a bundled Codex skill for image editing.

Enables AI agents to drive a user's own signed-in Google NotebookLM (Gemini Notebook) account through 51 MCP tools, covering notebook and source management, grounded chat with numbered citations, fast and deep research, and generating or downloading audio/video overviews, slide decks, quizzes, flashcards, mind maps, infographics, reports and data tables. It runs over stdio or streamable HTTP on localhost and sends progress notifications for long-running jobs.

Enables small models to turn a short brief into complete HTML pages or looping GIFs with typography, palette, borders, motion, and validation already decided. It also lets agents list styles, retrieve style rules, create assets, validate HTML, and access reference examples.

Enables AI agents to generate images, videos, and lip-sync media, and to query wallet balances via the Open Generative Studio instance.

Enables assistants to publish readable replies and status updates to e-ink displays and Home Assistant, with switchable characters and state retrieval through MCP tools.

Exposes two tools over stdio or HTTP that let AI agents read display geometry and capture full-screen, per-display, or region screenshots in PNG or JPEG. Runs as a VS Code extension or a standalone MCP server usable by Claude Code, Cursor, Cline and other clients.

Enables taking screenshots of the entire desktop or specific windows, with automatic clipboard integration and support for Windows, macOS, and Linux.

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.

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Provider-neutral Vision MCP Server — image analysis via 10 inference providers through a single MCP server.

Enables AI coding agents to perform end-to-end medical image analysis locally, from inspecting CT/MRI/X-ray studies and running containerized segmentation models like MedSAM2, TotalSegmentator, and HD-BET to refining masks, measuring volumes, and writing reports. It pairs preset or custom guideline protocols with a code-customizable viewer that renders images back to agents as annotated PNGs and to humans as interactive HTML.

Enables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.

Exposes Open Video Guide functions to MCP clients, enabling conversion of tutorial videos into illustrated, verifiable guides with timestamps, evidence, and review states.