College Football Analytics
An MCP server providing access to college football statistics sourced from the College Football Data API within Claude Desktop.
What is College Football Analytics?
College Football Analytics is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server providing access to college football statistics sourced from the college football data api within claude desktop.
An MCP server providing access to college football statistics sourced from the College Football Data API within Claude Desktop.
This server falls under the Analytics category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- An MCP server providing access to college football statistic
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx cfbdConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use College Football Analytics
The College Football Data MCP Server connects Claude Desktop to the College Football Data API (collegefootballdata.com), giving AI assistants direct access to comprehensive NCAA football statistics. It exposes nine query tools covering games, drives, plays, play-level stats, team records, rankings, win probability, and advanced box scores, plus five built-in prompt templates for guided analysis. Sports analysts, fantasy football enthusiasts, and researchers can query decades of college football data through natural language without writing any API code.
Prerequisites
- Python 3.10+ and the UV package manager installed (`pip install uv` or via brew)
- A free College Football Data API key from collegefootballdata.com/key
- Claude Desktop or another MCP-compatible client installed
- Git to clone the repository
Obtain a College Football Data API key
Register for a free account at collegefootballdata.com/key to get your CFB_API_KEY. This key is required for all data queries.
Install via Smithery (recommended)
The fastest installation method is through Smithery, which automatically configures Claude Desktop for you.
npx -y @smithery/cli install cfbd --client claudeManual installation: clone and set up the environment
Alternatively, clone the repository and create a virtual environment using UV.
git clone https://github.com/lenwood/cfbd-mcp-server.git
cd cfbd-mcp-server
uv venv
source .venv/bin/activate
uv pip install -e .Create a .env file with your API key
Create a .env file in the project root containing your College Football Data API key.
echo 'CFB_API_KEY=your_api_key_here' > .envConfigure Claude Desktop manually (if not using Smithery)
Add the server to your Claude Desktop configuration file at ~/Library/Application Support/Claude/claude_desktop_config.json.
{
"mcpServers": {
"cfbd": {
"command": "uv",
"args": ["run", "cfbd-mcp-server"],
"cwd": "/path/to/cfbd-mcp-server",
"env": {
"CFB_API_KEY": "your_api_key_here"
}
}
}
}Restart Claude Desktop and verify
Restart Claude Desktop and ask it to list the available college football tools to confirm the server is connected.
College Football Analytics Examples
Client configuration
Manual Claude Desktop configuration for the cfbd-mcp-server using UV to run the Python server.
{
"mcpServers": {
"cfbd": {
"command": "uv",
"args": ["run", "cfbd-mcp-server"],
"cwd": "/Users/yourname/cfbd-mcp-server",
"env": {
"CFB_API_KEY": "your_cfb_api_key_here"
}
}
}
}Prompts to try
Sample queries using the nine available tools and five built-in prompt templates.
- "What was the largest upset among FCS games during the 2014 season?"
- "Show me Michigan vs Ohio State head-to-head records for the last 10 years"
- "Analyze Alabama's win probability trends throughout the 2023 season"
- "What were the top-ranked teams in college football week 10 of 2022?"
- "Give me the advanced box score for the 2023 CFP National Championship game"
- "How many rushing yards did Georgia average per drive in the 2022 season?"Troubleshooting College Football Analytics
API requests return 401 Unauthorized errors
Verify your CFB_API_KEY is correctly set in both the .env file and the MCP client's env block. Keys are available free from collegefootballdata.com/key — ensure there are no extra spaces or quotes around the key value.
The server fails to start with 'uv: command not found'
Install the UV package manager with `pip install uv` or `brew install uv` on macOS. Alternatively, replace `uv run` with `python -m cfbd_mcp_server` in the MCP config after activating the project's virtual environment.
Queries return no data for recent seasons
The College Football Data API updates on a delay during the season. Check collegefootballdata.com for the latest available data week, and ensure you are querying with a valid year parameter that the API supports.
Frequently Asked Questions about College Football Analytics
What is College Football Analytics?
College Football Analytics is a Model Context Protocol (MCP) server that mcp server providing access to college football statistics sourced from the college football data api within claude desktop. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install College Football Analytics?
Follow the installation instructions on the College Football Analytics GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with College Football Analytics?
College Football Analytics works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is College Football Analytics free to use?
Yes, College Football Analytics is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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