Sports Trading Card Agent

Real-time sports card pricing, market analysis, arbitrage detection, grading ROI, investment advice, and player stats (NBA/NFL/MLB). 9 tools for AI agents helping collectors and investors.

GitHub

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

ToolDescription
card_price_lookupReal-time sold and active prices from eBay. Supports any sport, brand, year, or grading.
card_market_analysisTrend analysis comparing sold vs asking prices. Detects arbitrage opportunities where cards are listed below market value.

Player Stats

ToolDescription
player_stats_lookupMulti-sport player stats (NBA/NFL/MLB) with card market insights based on performance.
nfl_stats_lookupNFL passing, rushing, receiving, and defensive stats with card market insights.
mlb_stats_lookupMLB batting (AVG, HR, RBI, OPS) and pitching (ERA, K, WHIP) stats with card insights.

Analysis & Strategy

ToolDescription
grading_roi_calculatorCalculates whether grading a card is profitable. Compares raw vs graded prices for PSA, BGS, and SGC with fee-adjusted ROI.
card_investment_advisorBuy/sell/hold recommendations combining market trends with player performance data across all 3 sports.
trending_playersIdentifies NBA players with breakout performances whose cards are likely rising in value.
vintage_card_analysisEra-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

pip install sports-card-agent

Run the server

sports-card-agent

Use with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "sports-card-agent": {
      "command": "sports-card-agent"
    }
  }
}

Use with Claude Code

Add to your .mcp.json:

{
  "mcpServers": {
    "sports-card-agent": {
      "command": "sports-card-agent"
    }
  }
}

Configuration

Create a .env file or set environment variables:

# 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

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

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