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College Football Data MCP Server

@MCP-Mirror

代码仓库

基本信息

分类

数据与分析

传输方式

stdio

作者

MCP-Mirror

关于 College Football Data MCP Server

Mirror of

#college-football#data-server#mcp-server

College Football Data MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "lenwood_cfbd-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "cfbd",
        "--client",
        "claude"
      ]
    }
  }
}

College Football Data MCP Server 工具

9

Retrieve game data

Get team records

Access team game statistics

Query play-by-play data

Analyze drive information

View play statistics

Check team rankings

See win probabilities

Access detailed game statistics and analytics

概览

What is College Football Data MCP Server?

An MCP server that provides AI assistants with access to comprehensive college football statistics sourced from the College Football Data API. It enables users to query stats using natural language within Claude Desktop.

How to use College Football Data MCP Server?

Install via Smithery or clone the repository, set up a Python 3.11+ virtual environment with UV, and add your College Football Data API key to a .env file. Then configure the server in Claude Desktop's claude_desktop_config.json.

Key features of College Football Data MCP Server

  • Provides schema documentation for games, records, plays, drives, rankings.
  • Offers tools to query endpoints like get-games, get-records, get-plays.
  • Includes pre-built prompts for game, team, trend, and rivalry analysis.
  • Users can run queries using natural language.
  • Uses the free College Football Data API (with rate limits).

Use cases of College Football Data MCP Server

  • Get detailed analysis of a specific college football game.
  • Compare the season performances of two teams.
  • Analyze historical rivalry matchups.
  • Review team rankings and pregame win probabilities.
  • Study play-by-play data and drive summaries.

常见问题

1

What are the prerequisites for using this server?

Python 3.11 or higher, the UV package manager, and a free College Football Data API key.

2

What are the API limits?

The free tier has limited requests per minute. Patreon subscribers to College Football Data get higher rate limits.

3

How do I troubleshoot common issues?

Verify your API key in both the `.env` and `claude_desktop_config.json` files, check for rate limiting, and confirm internet connectivity.

4

Can I update the server after installation?

Yes, pull the latest files, uninstall the existing package, delete build artifacts, reinstall the package, and restart the server.

5

Is there a sample query I can try?

Yes. Asking "What was the largest upset among FCS games during the 2014 season?" returns a detailed analysis, including Eastern Washington defeating Washington.

评论

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