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by keiver • Uncategorized
An MCP server that tiles large images and captures full web pages to provide LLMs with full-resolution vision without downscaling loss.
Perform visual QA on web pages by capturing and analyzing full-resolution screenshots to detect layout and styling issues.
Test mobile responsive designs by capturing pages with mobile emulation and retina scaling.
Analyze large, detailed images like diagrams or infographics without losing critical details due to downscaling.
This MCP server enables large language models to analyze high-resolution images and full web pages by splitting them into tiles that fit within model-specific token and resolution limits. It supports capturing web pages with headless Chrome, including mobile emulation, and generates interactive HTML previews with token estimates. The tiling approach preserves image details that would otherwise be lost due to automatic downscaling, improving visual QA, responsive testing, and detailed image analysis workflows.
Split images into optimally-sized tiles for LLM vision analysis, or capture web page screenshots and tile them. MANDATORY two-phase workflow — DO NOT skip Phase 1: Phase 1 (REQUIRED first): Provide ONLY the image source (filePath, sourceUrl, url, etc). DO NOT include preset, tileSize, or outputDir. Returns a model comparison table with token estimates and an outputDir. You MUST present this table to the user and ask which preset they prefer. DO NOT select a preset yourself — the user decides. If you must auto-select, always use the cheapest option. Phase 2: Call again with the user's chosen preset + the outputDir from Phase 1. Re-include your original image source (filePath, sourceUrl, etc.). For captures, use screenshotPath from Phase 1 instead of url. Returns tile summary with metadata and content hints (no tile images). Use tilesDir + start/end to fetch only the tiles you need. Stop after Phase 1 if you only need the screenshot (capture mode) or comparison data. 4 tiling presets available: - "claude": 1092px tiles, ~1590 tokens/tile - "openai": 768px tiles, ~765 tokens/tile - "gemini3": 1536px tiles, ~1120 tokens/tile - "gemini": 768px tiles, ~258 tokens/tile Supports: local files (filePath), remote images (sourceUrl), data URLs, base64, and web page capture (url — Chrome required). Tiles saved as WebP (default) or PNG. Auto-downscales images over 10000px by default. TOKEN COST NOTE: The get-tiles mode returns image tiles as inline base64, consuming significantly more tokens than typical text-only MCP tools. Each tile costs ~258-1590 tokens depending on preset. Use the Phase 2 summary and tile hints to fetch only non-blank, relevant tiles.
Tile a local image and analyze every tile at full resolution
Capture a web page screenshot via Chrome, tile it, and analyze each tile
Supported vision model presets with tile sizes and per-tile token estimates
Quick reference: workflow, presets, and tips for the image tiler
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