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MCP Server for NBA Stats Predictor Application

MCP Server for NBA Stats Predictor Application

Local
github.com/dhrbtjr0331Games & Entertainment2Updated 79w ago

About MCP Server for NBA Stats Predictor Application

An MCP server for an NBA stats predictor application that provides forecasts of player performance in upcoming games. It is intended for use with Claude Desktop and relies on data analysis and statistical modeling.

Key features

  1. 01Forecasts player performance
  2. 02Uses real-time data analysis
  3. 03Uses statistical modeling
  4. 04Connects to Claude Desktop

Use cases

  1. 01Getting player forecasts for upcoming games
  2. 02Using predictions through Claude Desktop

MCP support

Exposes NBA player performance predictions to MCP clients such as Claude Desktop.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Server for NBA Stats Predictor Application

An MCP-powered tool for the NBA stats predictor app that generates player performance forecasts using real-time data analysis and advanced statistical modeling.

Demo

Installation

Prerequisites
  • Python 3.8+
  • pip
  • Claude Desktop
Step-by-Step Setup
  1. Clone this repository onto your local device

  2. Navigate to the project directory:

    cd nba-stats-predictor-application
    
  3. Create a virtual environment:

    python3 -m venv venv
    
  4. Activate the virtual environment:

    source venv/bin/activate
    
  5. Install dependencies:

    pip install -r requirements.txt
    
  6. Download the necessary data:

    python3 data_pipeline/download_data.py
    
  7. Train the prediction model:

    python3 models/train_model.py
    
  8. Start the FastAPI server:

    uvicorn api.fastapi_server:app --reload
    
  9. Open a new terminal

  10. Return to the project directory

  11. Install UV package manager:

    curl -LsSf https://astral.sh/uv/install.sh | sh
    
  12. Restart the terminal in this directory

  13. Run the MCP server:

    uv run mcp_main.py
    
  14. Open another new terminal

  15. Configure Claude Desktop:

    code ~/Library/Application\ Support/Claude/claude_desktop_config.json
    

    Note: If the file doesn't exist, create it.

  16. Add the following configuration to claude_desktop_config.json:

    {
        "mcpServers": {
            "NBA-stats-predictor": {
                "command": "/PATH/TO/PROJECT/DIRECTORY/.venv/bin/uv",
                "args": [
                    "--directory",
                    "/PATH/TO/PROJECT/DIRECTORY/",
                    "run",
                    "mcp_main.py"
                ]
            }
        }
    }
    

    Remember to replace /PATH/TO/PROJECT/DIRECTORY/ with the actual path to your project.

  17. You should now be able to use this MCP tool on Claude Desktop.

Usage

Once configured, you can use the NBA stats predictor tool in Claude Desktop to get predictions for player performance in upcoming games.

Troubleshooting

  • Make sure all paths in the configuration are correct
  • Ensure the virtual environment is activated before running commands
  • Check that all dependencies are properly installed
  • Verify that the FastAPI server is running before using the MCP tool

Comments

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