
NBA
Provides access to comprehensive NBA data including live game scores, player stats, team standings, and historical information through the NBA's official API.
Access comprehensive NBA stats and live game data through a Python server using Model Context Protocol. This project delivers real-time scoreboard updates, play-by-play action, player info, career stats, team standings, game logs, and schedules. It bridges applications with NBA’s official API, offering detailed live and historical basketball information. Tools cover everything from active player lists to team stats by name and comprehensive game results. Built with reliable data handling and input validation, it supports efficient access to NBA data for analysis, app development, or fan engagement. This server simplifies working with NBA data in various projects.
What it does
- Fetch live NBA scoreboards and game results
- Get real-time box scores and play-by-play data
- Query player career statistics and game logs
- Access team standings and game histories
- List active NBA players and their info
- Retrieve team statistics by name
Best for
About NBA
NBA is a community-built MCP server published by obinopaul that provides AI assistants with tools and capabilities via the Model Context Protocol. Access real-time NBA stats, including LeBron James statistics, Luka Doncic and Anthony Edwards stats, with live updates It is categorized under developer tools, analytics data.
How to install
You can install NBA in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
NBA is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
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)
- Clone this repository
git clone https://github.com/obinopaul/nba-mcp-server.git
cd nba-mcp-server
- Install dependencies
pip install -r requirements.txt
- Build the Docker image
docker build -t nba_mcp_server .
- Run the Docker container
docker run -d -p 5000:5000 --name nba_mcp_server nba_mcp_server
- 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
- Clone this repository
git clone https://github.com/obinopaul/nba-mcp-server.git
cd nba-mcp-server
- Create a new environment
conda create --name your_env_name python=3.13
conda activate your_env_name
- Install dependencies
pip install -r requirements.txt
- Run NBA mcp server on the terminal
mcp run nba_server.py
- 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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