NBA MCP Server

A Python server implementing Model Context Protocol (MCP) for NBA statistics and live game data.

Overview

This server provides a set of tools for accessing NBA data through the NBA API. It serves as a bridge between applications and the NBA's data services, offering both live game information and historical statistics.

Features

• Live game data (scoreboard, box scores, play-by-play)
• Player information and career statistics
• Team game logs and statistics
• League standings
• Game results and schedules

Tools

Live Game Data

• nba_live_scoreboard

  • Fetch today's NBA scoreboard (live or latest)
  • Returns game IDs, start times, scores, and broadcast details

• nba_live_boxscore

  • Fetch real-time box score for a given NBA game ID
  • Provides detailed player and team statistics

• nba_live_play_by_play

  • Retrieve live play-by-play actions for a specific game
  • Includes scoring plays, fouls, timeouts, and substitutions

Player Information

• nba_common_player_info

  • Retrieve basic information about a player
  • Includes biographical data, height, weight, team, position

• nba_player_career_stats

  • Obtain a player's career statistics
  • Available in different formats (per game, totals, per 36 minutes)

• nba_list_active_players

  • Return a list of all currently active NBA players

• nba_player_game_logs

  • Obtain a player's game statistics within a specified date range

Team Data

• nba_team_game_logs_by_name

  • Fetch a team's game logs using the team name
  • Avoids needing to know the team's numeric ID

• nba_fetch_game_results

  • Fetch game results for a given team ID and date range

• nba_team_standings

  • Fetch NBA team standings for a given season and season type

• nba_team_stats_by_name

  • Fetch team statistics using the team name
  • Supports different aggregation methods (totals, per game, etc.)

• nba_all_teams_stats

  • Fetch statistics for all NBA teams across multiple seasons

Schedule Information

• nba_list_todays_games
  • Returns scoreboard data for any specific date

Technical Details

The server is built on:

• NBA API (nba_api) Python package
• MCP for API interface
• Pydantic for input validation
• Pandas for data manipulation

Usage

The server is implemented using the MCP framework and can be run as a standalone service.

# Start the server
python nba_server.py
# or
mcp run nba_server.py

Configuration

• The server runs with a 30-second timeout for more reliable operation
• Signal handlers are implemented for graceful shutdown (Ctrl+C)

Usage with Claude Desktop

Option 1: Using Docker (Recommended)

1. Clone this repository

git clone https://github.com/obinopaul/nba-mcp-server.git
cd nba-mcp-server

2. Install dependencies

pip install -r requirements.txt

3. Build the Docker image

docker build -t nba_mcp_server .

4. Run the Docker container

docker run -d -p 5000:5000 --name nba_mcp_server nba_mcp_server

5. Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "nba_mcp_server": {
      "command": "docker",
      "args": [
        "exec",
        "-i",
        "nba_mcp_server",
        "python",
        "nba_server.py"
      ]
    }
  }
}

Option 2: Direct Python Execution

1. Clone this repository

git clone https://github.com/obinopaul/nba-mcp-server.git
cd nba-mcp-server

2. Create a new environment

conda create --name your_env_name python=3.13
conda activate your_env_name

3. Install dependencies

pip install -r requirements.txt

4. Run NBA mcp server on the terminal

mcp run nba_server.py

5. Add this to your claude_desktop_config.json, adjusting the Python path as needed:

{
  "mcpServers": {
    "nba_mcp_server": {
      "command": "/path/to/your/python",
      "args": [
        "/path/to/nba_server.py"
      ]
    }
  }
}

After adding your chosen configuration, restart Claude Desktop to load the NBA server. You'll then be able to use all the NBA data tools in your conversations with Claude.

License

This MCP server is available under the MIT License.