Sports Card Agent

io.github.rjexile由 GitHub 账号 rjexile 发布v1.0.1更新于 Oct 24, 2026

Sports card pricing, market analysis, grading ROI, and player stats (NBA/NFL/MLB)

已验证STDIO仅桌面金融数据与分析

概览

AI 生成的概览

让助手查询体育球星卡价格、市场趋势、评级投资回报率以及 NBA/NFL/MLB 球员数据。

可以做什么
提供九个工具用于球星卡研究：eBay 成交价与在售价查询、含套利识别的市场趋势分析、PSA、BGS、SGC 的评级投资回报率计算、买入/卖出/持有建议、热门球员提醒，以及覆盖 40 多个 2000 年前系列的复古卡分析。球员数据工具覆盖 NBA、NFL、MLB 表现并结合卡市背景。它在本地运行，未配置 API 密钥时可使用模拟数据启动。
适用场景
适合需要为某张卡定价、判断评级费用是否划算、比较裸卡与评级卡价值，或把球员近期表现与卡价走势联系起来的场景。更适合收藏者和卖家反复做卡片调研，而非一次性查询。
运行要求
作为本地 Python 进程运行，从 PyPI 安装（pip install sports-card-agent），通过 stdio 通信，仅支持桌面端。可选凭据：球员数据需要 BALLDONTLIE_API_KEY，eBay 价格需要 EBAY_APP_ID 与 EBAY_CERT_ID。未配置密钥时回退到模拟数据。获取实时数据需要网络访问。
安装前请注意
需要三个密钥：BALLDONTLIE_API_KEY、EBAY_APP_ID 和 EBAY_CERT_ID；请放在环境变量或 .env 文件中，不要外泄。未配置密钥时服务器返回模拟数据，价格和建议可能是虚构的，而非真实数据。投资建议与套利信号属于模型生成内容，并非经过核实的理财指导，卡价依赖第三方 eBay 与数据 API。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Sports Card Agent，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

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

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_idEBAY_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.gitcd sports-card-agentpython -m venv venvsource venv/Scripts/activate  # Windowspip install -e .python test_all.py  # Run all 29 tests

License

MIT

来源：README.md，提交 9e59a60

工具

0
SourceWeft 尚未在沙箱中启动过该软件包，因此其工具未知。

版本历史

1
  1. v1.0.1最新Sep 16, 2026

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