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lenwood/cfbd-mcp-server: An MCP server enabling CFBD API queries within Claude Desktop.

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.

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

Users can run queries using natural language.

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:

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

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:
  1. Create a .env file in the project root and add your API key:
CFB_API_KEY=your_api_key_here
  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:
  1. Create a .env file in the project root and add your API key:
CFB_API_KEY=your_api_key_here

Start the server:

Connecting with Claude Desktop
  1. Open your Claude Desktop configuration at:

  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.

  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
  1. Close and restart Claude Desktop

Access schema documentation for all endpoints:

Query endpoints directly:

Pre-built analysis templates:

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

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:
  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to your fork
  5. Submit a pull request
  1. API Key Errors

  2. Rate Limiting

  3. Connection Issues

This project is licensed under the MIT License - see the LICENSE file for details.


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