# Project Research Summary

**Project:** Screen Timelapse MCP Server
**Domain:** MCP Server -- Desktop Screen Capture and Timelapse Tool for AI Agent Visual Debugging
**Researched:** 2026-04-12
**Confidence:** HIGH

## Executive Summary

This project is an MCP (Model Context Protocol) server that captures timed sequences of desktop/window screenshots and compiles them into grid images that AI agents can consume via their vision capabilities. The expert approach for this type of tool is a single-process Node.js server communicating over stdio JSON-RPC, with a clear separation between the MCP transport layer, capture engine, and image processing pipeline. The stack is well-established: the official MCP TypeScript SDK for protocol handling, node-screenshots for native cross-platform capture (with window enumeration and region cropping), and sharp for high-performance image compositing into grid layouts.

The recommended approach is to build the MCP server skeleton first with an ironclad no stdout pollution guarantee, then layer in desktop capture, then grid compilation with aggressive image size budgeting, and finally add targeting refinements (window/region capture) and diagnostic features (delta highlighting, GIF export). The core value proposition -- a grid of timestamped screenshots that an AI agent can read in a single image -- is straightforward to implement but requires careful attention to image sizing for LLM consumption and memory management during grid assembly.