Server data from the Official MCP Registry
Sports card pricing, market analysis, grading ROI, and player stats (NBA/NFL/MLB)
Sports card pricing, market analysis, grading ROI, and player stats (NBA/NFL/MLB)
Valid MCP server (1 strong, 4 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
6 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Set these up before or after installing:
Environment variable: EBAY_APP_ID
Environment variable: EBAY_CERT_ID
Environment variable: BALLDONTLIE_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-rjexile-sports-card-agent": {
"env": {
"EBAY_APP_ID": "your-ebay-app-id-here",
"EBAY_CERT_ID": "your-ebay-cert-id-here",
"BALLDONTLIE_API_KEY": "your-balldontlie-api-key-here"
},
"args": [
"sports-card-agent"
],
"command": "uvx"
}
}
}From the project's GitHub README.
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.
| 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. |
| 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. |
| 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. |
pip install sports-card-agent
sports-card-agent
Add to your claude_desktop_config.json:
{
"mcpServers": {
"sports-card-agent": {
"command": "sports-card-agent"
}
}
}
Add to your .mcp.json:
{
"mcpServers": {
"sports-card-agent": {
"command": "sports-card-agent"
}
}
}
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.
Once connected, any AI agent can ask:
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)
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
MIT
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