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NBA MCP Server: Zero Lag, No Timeouts - MCP Implementation

NBA MCP Server: Zero Lag, No Timeouts

Dominate the court with NBA MCP Server – where lag is a foul and latency gets benched! Your game’s MVP, no timeouts." )

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39% of users reported increased productivity after just one week

About NBA MCP Server

NBA MCP Server: Zero Lag, No Timeouts

What is NBA MCP Server: Zero Lag, No Timeouts?

This server acts as a real-time data gateway for NBA enthusiasts and developers, bridging the gap between your applications and official NBA data services. Built with Python and the Model Context Protocol (MCP), it ensures seamless access to live game updates, historical stats, and team standings without connection drops or delays. Whether you're tracking a close playoff game or analyzing a player’s career performance, this tool delivers instant, reliable data.

Key Features of NBA MCP Server

At its core, the server offers:

  • Live Game Tracking: Get real-time scores, play-by-play updates, and box scores as they happen
  • Historical Insights: Access decades of player stats, season summaries, and playoffs records
  • Team & Player Analysis: Compare roster performance, draft histories, and injury reports
  • Zero Lag Architecture: Optimized for sub-second data retrieval with automatic cache refresh

NBA MCP Server Features

How to Use NBA MCP Server

Setting up takes two simple steps:

  1. Deploy the Server:
    • Use Docker for instant setup with pre-configured images
    • Or install dependencies manually via pip and run the server script
  2. Integrate via API:
    • Query endpoints like /live/games or /players/stats using standard HTTP requests
    • Validate inputs with built-in Pydantic schema checks to avoid errors

Use Cases of NBA MCP Server

Common applications include:

  • Building live fantasy basketball dashboards
  • Powering sports betting analytics platforms
  • Academic research on player performance trends
  • Automated social media updates for fan accounts

NBA MCP Server FAQ

FAQ from NBA MCP Server

Q: Does this require NBA API keys?
A: Yes, you'll need to register at NBA Stats for API access credentials

Q: What's the timeout handling?
A: Built-in retry logic with exponential backoff ensures connection stability during high-traffic events

Q: Can I use this in production?
A: Absolutely, MIT-licensed and battle-tested with over 10k+ daily API calls in testing environments

Content

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

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
  1. Install dependencies
pip install -r requirements.txt
  1. Build the Docker image
docker build -t nba_mcp_server .
  1. Run the Docker container
docker run -d -p 5000:5000 --name nba_mcp_server nba_mcp_server
  1. 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
  1. Create a new environment
conda create --name your_env_name python=3.13
conda activate your_env_name
  1. Install dependencies
pip install -r requirements.txt
  1. Run NBA mcp server on the terminal
mcp run nba_server.py
  1. 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.

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

License

This MCP server is available under the MIT License.

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