Sports Card Agent
<!-- mcp-name: io.github.rjexile/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