MCP Connector

Access College Football Data via API

An MCP server that connects Claude Desktop to the College Football Data API for natural-language stats queries.

Works with github

88
Spark score
out of 100
Updated May 2025
Source checked Sep 24, 2026
Version 1.0.0
Models
universal

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Why it matters

Leverage the College Football Data API V2 to query game results, team records, player statistics, and rankings. This MCP server provides access to comprehensive sports data for analysis and insights.

Outcomes

What it gets done

01

Query game results and team records

02

Access player statistics and play-by-play data

03

Retrieve team rankings and win probability forecasts

04

Analyze historical game performance and rivalries

Source

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Open source

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Capabilities

Tools your agent gets

get-games

Retrieve game data from college football statistics

get-records

Get team records and historical performance data

get-games-teams

Access game team statistics and performance metrics

get-plays

Request play-by-play data for college football games

get-drives

Analyze drive information and scoring sequences

get-play-stats

View detailed play statistics and analytics

get-rankings

Check team rankings and standings

get-pregame-win-probability

View win probability forecasts for upcoming games

get-advanced-box-score

Access detailed game statistics and advanced analytics

Overview

An MCP server that connects Claude Desktop to the College Football Data API V2, exposing game results, team records, plays, drives, rankings, and win-probability data as tools and resources for natural-language queries. Use it to explore college football stats and history conversationally in Claude Desktop; it requires a CFBD API key and is limited to the data the CFBD API provides, not live odds or betting.

What it does

An MCP server that connects Claude Desktop to the College Football Data API V2, letting an AI assistant query college football statistics in natural language - game results, team records, player statistics, play-by-play data, drive summaries, rankings, and win-probability metrics.

When to use - and when NOT to

Use it when you want to ask natural-language questions about college football history and stats - for example finding a season's biggest upset, comparing two teams' performance, or pulling a specific game's advanced box score - without hand-writing API calls. It needs a College Football Data API key to work at all, and its scope is limited to what the underlying API covers (games, records, plays, drives, rankings, win probability) - it is not a live-odds or betting tool.

Capabilities

  • Resources exposing schema documentation for each endpoint: schema://games, schema://records, schema://games/teams, schema://plays, schema://drives, schema://play/stats, schema://rankings, schema://metrics/wp/pregame, schema://game/box/advanced
  • Tools for querying data directly: get-games, get-records, get-games-teams, get-plays, get-drives, get-play-stats, get-rankings, get-pregame-win-probability, get-advanced-box-score
  • Pre-built analysis prompts: analyze-game, analyze-team, analyze-trends, compare-teams, analyze-rivalry
  • Natural-language querying - for example asking for the largest FCS upset of a given season and getting back a reasoned answer that cites specific games and win probabilities, such as Eastern Washington's 59-52 win over Washington in 2014, where post-game stats put Eastern Washington's win probability at only 1.4%
  • Rate limiting on the free API tier, with higher limits available to CFBD Patreon subscribers

How to install

Requires Python 3.11+, the UV package manager, and a College Football Data API key from collegefootballdata.com/key. Install via Smithery:

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

Or manually: clone the repository, create a virtual environment with uv venv, install with uv pip install -e ., and add the key to a .env file as CFB_API_KEY=your_api_key_here. Start the server with uv run cfbd-mcp-server, then add it to Claude Desktop's claude_desktop_config.json under mcpServers, pointing command at uv with --directory, run, and cfbd-mcp-server as arguments, and CFB_API_KEY set in env. After restarting Claude Desktop, a successful install shows an "Add from cfbd-mcp-server" option in the text box's plus-sign menu. It is released under the MIT License. To update later, pull the latest changes with git pull, reinstall with uv pip install -e ., and restart Claude Desktop. If queries fail, check that the API key is set correctly in both the .env file and claude_desktop_config.json and is still valid at collegefootballdata.com.

Who it's for

College football fans, analysts, and researchers who want to explore historical stats, rankings, and game data conversationally in Claude Desktop instead of querying the CFBD API directly.

Source README

College Football Data MCP Server

An MCP server implementation providing access to college football statistics sourced from the College Football Data API V2 within Claude Desktop.

Python Version CFBD API Version MIT License smithery badge

Overview

This Model Context Protocol (MCP) server enables AI assistants and applications to:

  • Query comprehensive college football statistics and data
  • Access game results, team records, and player statistics
  • Analyze play-by-play data and drive summaries
  • View rankings and win probability metrics
  • Compare team performances and generate insights

Users can run queries using natural language.

Sample output

Q. What was the largest upset among FCS games during the 2014 season?

A. Let me help find the biggest FCS upset from 2014. I'll look through the games data, focusing on games between FCS teams where there was a significant gap in team strength and an unexpected outcome.

The data suggests there were several notable upsets in FCS during 2014, but one that stands out was Eastern Washington defeating Washington 52-59 on September 6th, 2014. This was particularly significant because:

  1. Washington was an FBS team from the Pac-12 conference
  2. The game was played at Washington's home stadium (Husky Stadium)
  3. Eastern Washington's win probability was only 1.4% according to the post-game stats
  4. The 59 points Eastern Washington scored was the most ever by an FCS team against a Pac-12 opponent
  5. Washington had been favored by multiple scores going into the game

Other notable FCS upsets from that season included:

  • North Dakota State defeating Iowa State 34-14
  • Bethune-Cookman defeating FIU 14-12
  • Northern Iowa nearly upsetting Iowa (lost 31-23)

However, Eastern Washington over Washington appears to be the largest upset of the 2014 FCS season when considering:

  • The difference in divisions (FCS vs FBS)
  • The caliber of the FBS opponent (Power 5 conference)
  • The scoring margin and offensive performance by the underdog
  • The historical significance as one of the highest-scoring FCS wins over a Power 5 team
  • The fact it happened on the road in a hostile environment

Prerequisites

Installation

Installing via Smithery

To install College Football Data Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install cfbd --client claude
  1. Clone this repository:
git clone https://github.com/yourusername/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
Manual Installation
  1. Clone this repository:
git clone https://github.com/yourusername/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

Usage

Running the Server

Start the server:

uv run cfbd-mcp-server
Connecting with Claude Desktop
  1. Open your Claude Desktop configuration at:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the server configuration:

{
    "mcpServers": {
        "cfbd-mcp-server": {
            "command": "uv",
            "args": [
                "--directory",
                "/full/path/to/cfbd-mcp-server",
                "run",
                "cfbd-mcp-server"
            ],
            "env": {
                "CFB_API_KEY": "xxx",
                "PATH": "/full/path/to/python"
            }
        }
    }
}
  1. Close then restart Claude Desktop

Once you restart you can confirm the installation by clicking on the plus sign in the lower left corner of the text box. If successful you'll see "Add from cfbd-mcp-server" as one of the menu options. Here's an example screenshot.

Screenshot of successful install

Updating after install

  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

For Windows:

rmdir /s /q build dist
del /s /q *.egg-info

For macOS:

rm -rf build dist *.egg-info
  1. Install the revised package and its dependencies
uv pip install -e .
uv sync --dev --all-extras

5.

uv run cfbd-mcp-server
  1. Close and restart Claude Desktop

Features

Resources

Access schema documentation for all endpoints:

  • schema://games - Game information and scores
  • schema://records - Team season records
  • schema://games/teams - Detailed team game data
  • schema://plays - Play-by-play information
  • schema://drives - Drive summaries and results
  • schema://play/stats - Individual play statistics
  • schema://rankings - Team rankings across polls
  • schema://metrics/wp/pregame - Pregame win probabilities
  • schema://game/box/advanced - Advanced box score statistics
Tools

Query endpoints directly:

  • get-games - Retrieve game data
  • get-records - Get team records
  • get-games-teams - Access team game statistics
  • get-plays - Query play-by-play data
  • get-drives - Analyze drive information
  • get-play-stats - View play statistics
  • get-rankings - Check team rankings
  • get-pregame-win-probability - See win probabilities
  • get-advanced-box-score - Access detailed game statistics and analytics
Prompts

Pre-built analysis templates:

  • analyze-game - Get detailed analysis of a specific game
  • analyze-team - Comprehensive single team analysis
  • analyze-trends - Analyze trends over a season
  • compare-teams - Compare performance of two teams
  • analyze-rivalry - Analyze historical rivalry matchups

API Limits

The College Football Data API is free to use but has rate limiting:

  • Free tier: Limited requests per minute
  • CFBD Patreon subscribers get higher rate limits
  • Use efficient querying patterns to avoid hitting limits
  • Handle rate limit errors gracefully

Development

Project Structure
cfbd-mcp-server/
├── README.md
├── pyproject.toml
└── src/
    └── cfbd_mcp_server/
        ├── .env
        ├── __init__.py
        ├── cfbd_schema.py
        ├── schema_helpers.py
        └── server.py
Setting Up for Development
  1. Clone the repository
  2. Install development dependencies:
uv pip install -e ".[dev]"
  1. Run tests:
pytest

Troubleshooting

Common Issues
  1. API Key Errors

    • Verify your API key is correctly set in both the .env and claude_desktop_config.json files
    • Check the key is valid at collegefootballdata.com
  2. Rate Limiting

    • Space out requests when possible
    • Consider Patreon subscription for higher limits
    • Implement caching for frequently accessed data
  3. Connection Issues

    • Verify internet connectivity
    • Check API status at collegefootballdata.com
    • Ensure proper error handling in your code
Getting Help

FAQ

Common questions

Discussion

Questions & comments · 0

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