Sports Trading Card Agent

Created By

rjexilea month ago

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.

# sports cards

# trading cards

Overview Content Tools Comments

Overview

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

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

Server Config

{
  "mcpServers": {
    "sports-trading-card-agent": {
      "command": "uvx",
      "args": [
        "sports-card-agent"
      ]
    }
  }
}

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