Sports Trading Card Agent
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Alternatives to Sports Trading Card Agent
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- FlicenseNot gradedqualityBmaintenanceEnables AI assistants to look up trading-card market values across Pokémon, Magic, sports and other TCG catalogs, including raw prices by condition, graded ladders, price history, trending movers and set checklists. It also calculates grading ROI — gem premiums, net profit after fees, expected value and break-even gem rates — so collectors can decide whether a card is worth submitting.-
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to access comprehensive sports data including football, basketball, American football, and hockey leagues via 11 tools, with no API key required.MIT
- AlicenseAqualityDmaintenanceProvides AI-powered sports betting intelligence including live odds, injury reports, and documented picks for NBA, NHL, and NCAAB. It enables AI agents to analyze line movements, win rates, and betting edges using real-time data from sportsbettingaianalyzer.com.1124 PyPI5MIT

@pokemontcgapi/mcpofficial
AlicenseAqualityBmaintenanceEnables agents to search and query Pokémon TCG cards and sets, retrieve priced card data with provenance, and identify cards from images through eight read-only tools.8371 npmMIT
satorntcg-mcp-serverofficial
AlicenseNot gradedqualityBmaintenanceEnables LLM clients to query live TCG inventory, pricing, alerts, profit and loss, and eBay listings directly through natural language tool calls.MIT- FlicenseNot gradedqualityBmaintenanceProvides access to TCGplayer trading card data, including search, product details, pricing, and market information, enabling natural language queries for card analysis.1-
TDQS
Scored across 9 tools
There is significant functional overlap between tools, particularly among the stats lookups (mlb_stats_lookup, nfl_stats_lookup, player_stats_lookup) which all provide similar player stats and card market insights, differing mainly by sport specificity. Additionally, card_market_analysis and card_price_lookup both retrieve pricing data, though with different focuses. The descriptions help clarify distinctions, but an agent could easily misselect between these overlapping tools.
Tool names mostly follow a consistent snake_case pattern with descriptive verb_noun or noun_verb structures (e.g., card_price_lookup, grading_roi_calculator). However, there is a minor inconsistency with trending_players (which uses an adjective_noun format) and player_stats_lookup (which overlaps in naming style with the sport-specific stats tools). Overall, the naming is readable and largely predictable.
With 9 tools, the count is well-scoped for a sports trading card agent, covering key areas like pricing, analysis, stats, and trends. Each tool serves a distinct niche within the domain, and the number is manageable without being overwhelming or insufficient for the server's purpose.
The tool set provides comprehensive coverage for sports card evaluation, including pricing, market analysis, stats, ROI calculation, and trend identification. A minor gap exists in the lack of tools for managing a card collection (e.g., adding, tracking, or valuing a personal inventory), but core workflows for investment advice and market research are well-supported.