# Sports Card Agent An MCP server that gives AI agents expert-level sports trading card data. Covers pricing, market analysis, arbitrage detection, grading ROI, investment advice, player stats (NBA/NFL/MLB), vintage card analysis, and trending player alerts. **9 tools. 3 sports. 40+ vintage sets. Zero manual research.** ## Tools ### Pricing & Market | Tool | Description | |------|-------------| | `card_price_lookup` | Real-time sold and active prices from eBay. Supports any sport, brand, year, or grading. | | `card_market_analysis` | Trend analysis comparing sold vs asking prices. Detects arbitrage opportunities where cards are listed below market value. | ### Player Stats | Tool | Description | |------|-------------| | `player_stats_lookup` | Multi-sport player stats (NBA/NFL/MLB) with card market insights based on performance. | | `nfl_stats_lookup` | NFL passing, rushing, receiving, and defensive stats with card market insights. | | `mlb_stats_lookup` | MLB batting (AVG, HR, RBI, OPS) and pitching (ERA, K, WHIP) stats with card insights. | ### Analysis & Strategy | Tool | Description | |------|-------------| | `grading_roi_calculator` | Calculates whether grading a card is profitable. Compares raw vs graded prices for PSA, BGS, and SGC with fee-adjusted ROI. | | `card_investment_advisor` | Buy/sell/hold recommendations combining market trends with player performance data across all 3 sports. | | `trending_players` | Identifies NBA players with breakout performances whose cards are likely rising in value. | | `vintage_card_analysis` | Era-specific analysis for pre-2000 cards. Covers 40+ iconic sets from 1909 T206 to 2000 Playoff Contenders with grade-based pricing. | ## Quick Start ### Install from PyPI ```bash pip install sports-card-agent ``` ### Run the server ```bash sports-card-agent ``` ### Use with Claude Desktop Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "sports-card-agent": { "command": "sports-card-agent" } } } ``` ### Use with Claude Code Add to your `.mcp.json`: ```json { "mcpServers": { "sports-card-agent": { "command": "sports-card-agent" } } } ``` ## Configuration Create a `.env` file or set environment variables: ```bash # eBay API (register free at developer.ebay.com) EBAY_APP_ID=your_app_id EBAY_CERT_ID=your_cert_id # Ball Don't Lie API (register free at app.balldontlie.io) BALLDONTLIE_API_KEY=your_api_key ``` The server works without API keys using mock data, so you can try it immediately. ## Example Queries Once connected, any AI agent can ask: - "What's a 2023 Topps Chrome Wembanyama rookie selling for?" - "Should I buy or sell my Patrick Mahomes rookie card?" - "Is it worth grading my 1986 Fleer Jordan?" - "Who are the trending NBA players whose cards are rising?" - "Analyze the market for Ken Griffey Jr 1989 Upper Deck rookie" - "What's the investment outlook on vintage 1952 Topps Mickey Mantle?" - "How is Shohei Ohtani performing this season and what does that mean for his cards?" ## Sports & Sets Covered **Sports:** Baseball, Basketball, Football, Hockey, Soccer **Player Stats:** NBA (all teams), NFL (all positions), MLB (batting + pitching) **Vintage Sets Include:** 1909 T206, 1933 Goudey, 1951 Bowman, 1952 Topps, 1954-55 Topps, 1958 Topps Football, 1961 Fleer Basketball, 1965 Topps Football, 1966 Topps Hockey, 1969 Topps, 1979 O-Pee-Chee, 1981 Topps Football, 1984 Topps Football, 1986 Fleer Basketball, 1986 Donruss, 1989 Upper Deck, 1993 SP, 1996 Topps Chrome, 1997 Metal Universe, 2000 Playoff Contenders, and more. **Grading Companies:** PSA, BGS, SGC (all service tiers with current pricing) ## Development ```bash git clone https://github.com/rjexile/sports-card-agent.git cd sports-card-agent python -m venv venv source venv/Scripts/activate # Windows pip install -e . python test_all.py # Run all 29 tests ``` ## License MIT