Image Tiler MCP Server vs Slideshot

tiler

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.