In-depth architectural comparison of the Image Tiler MCP Server and Runapi AI MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Image Tiler MCP Server
Multimedia Process · Local stdio
Quality: 55/100 (Good) | Auth: No auth required
Runapi AI MCP
Multimedia Process · Local stdio
Quality: 68/100 (Great) | Auth: API Key required
Verdict Summary: Choose Image Tiler MCP Server if you need specialized Multimedia Process tools running via a local process. Choose Runapi AI MCP if your workspace requires Multimedia Process integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Image Tiler MCP Server when:
You need dedicated capabilities in the Multimedia Process domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
You have access to required keys: TILER_ALLOWED_DIRS, TILER_DISABLE_URL_CAPTURE, CHROME_NO_SANDBOX.
Full-resolution vision for LLMs. Tiles large images and captures web pages via Chrome CDP so vision models process every detail without downscaling. Generates interactive HTML tile previews. Supports Claude, OpenAI, Gemini presets with per-model token math and entropy-based tile classification.
Unified AI model API for 130+ models across 18 providers. Browse models, check pricing, create image/video/music/audio tasks, poll results, check balance, and call LLM endpoints. Free catalog tools work without an API key. npx @runapi.ai/mcp
Category & Scope
Tools & Capabilities Breakdown
Image Tiler MCP Server Tools (1)
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.
Runapi AI MCP Tools (9)
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Image Tiler MCP Server is categorized under Multimedia Process and uses a local stdio subprocess. In contrast, Runapi AI MCP belongs to Multimedia Process using local stdio subprocess. Select Image Tiler MCP Server when you need capabilities focused on multimedia process and Runapi AI MCP when you require tools for multimedia process.
List RunAPI models from the embedded catalog. Optional filters: modality, service, or action.
get_model_info
Get supported endpoint, current runtime pricing, and input constraints for a RunAPI model slug. Add service and action when the model supports multiple endpoints.
list_actions
List RunAPI endpoint names grouped by output modality.
check_pricing
Return current runtime pricing for a RunAPI model/action pair.
search_prompts
Search RunAPI prompt examples by modality, category, tags, text query, model, or featured status. Free, no API key required.
check_balance
Return the authenticated RunAPI account balance and spending metrics.
create_task
Run a RunAPI operation with a caller-generated idempotency key. Asynchronous operations can optionally poll until completion.
get_task
Fetch the current status and latest payload for an existing RunAPI task.
login
Authenticate RunAPI by opening a browser PKCE login flow and saving the API key to ~/.config/runapi/config.json.