How to Track Top Cards by Sport or Category with OpenClaw
Track top cards by sport or category with OpenClaw and ToolRouter. Batch card market data.
Tool
OpenClaw processes card ranking queries in batch across multiple sports, eras, and collectible categories, returning normalized market data for card trading platforms, collector apps, or market analysis tools. Build comprehensive category-level market datasets with scheduled refresh runs.
Connect ToolRouter to OpenClaw
1Install the CLI
npm install -g toolrouter-mcp2Call tools directly from OpenClaw
toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp toolsSteps
Once connected (see setup above), use the Trading Cards tool:
- Specify the sports or categories to track
- Ask: "Use trading-cards to get top card rankings for NBA, NFL, and MLB"
- OpenClaw returns structured top-card data for all categories
- Normalize to a stable schema with sport, rank, player, card_name, rarity, recent_sale, and estimated_value
Example Prompt
Try this with OpenClaw using the Trading Cards tool
Use trading-cards to get the current top cards across NBA, NFL, MLB, and Pokémon categories. Return stable JSON with category, rank, player_or_character, card_name, set, year, rarity, recent_sale_price, currency, and estimated_value for all results.
Tips
- Lock the schema before your first batch run so all category results are directly comparable
- Tag each record with category and sport fields to support cross-category analysis in your platform
- Schedule daily refresh runs for active market monitoring — top card rankings shift quickly with player news