Back to MCP Catalog

College Football Data MCP Server

SportsPython
Access comprehensive college football statistics and data through the CFBD API
Available Tools

get-games

Retrieve college football game data including scores, teams, venues, and game dates

get-records

Get team season records including wins, losses, and conference standings

get-games-teams

Access detailed team statistics for specific games

get-plays

Query play-by-play data for detailed game analysis

get-drives

Analyze drive information including results, field position, and time of possession

get-play-stats

View detailed statistics for individual plays

get-rankings

Check team rankings across different polls and ranking systems

get-pregame-win-probability

Access pregame win probability predictions

get-advanced-box-score

View detailed game statistics and advanced analytics

analyze-game

Get detailed analysis of a specific college football game

analyze-team

Generate comprehensive analysis of a single team's performance

analyze-trends

Analyze trends over a college football season

compare-teams

Compare performance metrics between two college football teams

analyze-rivalry

Analyze historical rivalry matchups between college football teams

College Football Data provides access to a wealth of college football statistics and analytics through the College Football Data API V2. This integration enables AI assistants to query game results, team records, player statistics, play-by-play data, rankings, and win probability metrics. With this tool, users can analyze historical college football data, compare team performances, and generate insights using natural language queries. The server connects to the official CFBD API, providing up-to-date and accurate information for both casual fans and serious analysts.

Overview

College Football Data MCP Server provides access to comprehensive college football statistics and data through the College Football Data API V2. This integration allows you to query game results, team records, player statistics, analyze play-by-play data, view rankings, and much more using natural language.

Prerequisites

Before installing the College Football Data MCP Server, ensure you have:

Installation Options

Option 1: Install via Smithery (Recommended)

The easiest way to install College Football Data for Claude Desktop is via Smithery:

npx -y @smithery/cli install cfbd --client claude

Option 2: Manual Installation

  1. Clone the repository:
git clone https://github.com/lenwood/cfbd-mcp-server
cd cfbd-mcp-server
  1. Create and activate a virtual environment:
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
  1. Install dependencies:
uv pip install -e .
  1. Create a .env file in the project root and add your API key:
CFB_API_KEY=your_api_key_here

Configuration

To connect with Claude Desktop:

  1. Open your Claude Desktop configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the server configuration as shown in the installation section below.

  3. Close and restart Claude Desktop.

  4. Verify installation by clicking the plus sign in the lower left corner of the text box. You should see "Add from cfbd-mcp-server" as one of the menu options.

Usage

Once installed, you can ask questions about college football data using natural language. For example:

  • "What was the largest upset among FCS games during the 2014 season?"
  • "Compare the offensive statistics of Alabama and Georgia in 2023"
  • "Show me the top 10 rushing leaders from the Big Ten conference last season"
  • "What was the win probability for Michigan against Ohio State at halftime in their 2021 matchup?"

Updating

To update the College Football Data MCP Server:

  1. Download the updated files:
cd cfbd-mcp-server
git pull
  1. Uninstall the existing package:
uv pip uninstall cfbd-mcp-server
  1. Delete existing build artifacts and metadata:

    • Windows: rmdir /s /q build dist and del /s /q *.egg-info
    • macOS: rm -rf build dist *.egg-info
  2. Install the revised package and its dependencies:

uv pip install -e .
uv sync --dev --all-extras
  1. Restart the server:
uv run cfbd-mcp-server
  1. Close and restart Claude Desktop.

API Limits

Be aware that the College Football Data API has rate limits. Excessive queries may result in temporary restrictions on your API key.

Related MCPs

Fantasy Premier League
SportsPython

Access and analyze Fantasy Premier League data

FirstCycling
SportsPython

Access comprehensive professional cycling data including riders, races, and results

Strava API
SportsPython

Access and analyze your Strava activity data

About Model Context Protocol

Model Context Protocol (MCP) allows AI models to access external tools and services, extending their capabilities beyond their training data.

Generate Cursor Documentation

Save time on coding by generating custom documentation and prompts for Cursor IDE.