r/CFBAnalysis

I’ve been using CFBD this offseason and wanted an easy way to connect the data to AI coding agents, so I built this:

https://github.com/jvorndran/fbs-cli

It’s basically like an MCP, but it uses a CLI instead, which is more token efficient and creates less context bloat. It currently supports all 71 CFBD GET endpoints and returns the data as YAML.

For example:

fbs games --year 2026 --week 1 --team Florida

You’ll still need your own CFBD API key, then you can set it up by running:

fbs auth

I’ve been using it with Codex in my own college football research workflows and it works pretty well. This article has some interesting evals comparing CLI tools with MCP if you’re curious about why I built it this way:

https://www.scalekit.com/blog/mcp-vs-cli-use

Would love any feedback or ideas for what to add next.

Hi all,

Season is close to coming up which means I break out my spreadsheets and try to predict things again.

I am really encouraged by what I could generate with AI this year but still find it falling short.

Just wanted to ask, for those who use it what have you found to be disappointing about trying to develop CFB analysis with AI?