NBA MCP Server
Provides NBA statistics and live game data using the Model Context Protocol (MCP).
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.
関連サーバー
AgentAuth
Auth0, but for agents. Identity and authentication service for AI agents.
AgentPay
x402 payment gateway for AI agents — 12 crypto data tools (price, whale activity, gas, TVL, Fear & Greed, Dune queries) paid per-call in USDC on Stellar or Base. No API keys, no subscriptions.
httpay-mcp
121 pay-per-call API tools for AI agents — crypto, weather, finance data via x402 micropayments (USDC on Base). Each call costs $0.001-$0.05.
mcp-cbr-rates
A Model Context Protocol (MCP) server that exposes public Bank of Russia (Центральный банк РФ, CBR) data — currency quotes, key rate, inflation and a compact macro snapshot — to AI agents.
FinMCP
Lightweight TypeScript Finance MCP server wrapping Yahoo Finance APIs. Plug real-time financial data — stocks, options, crypto, earnings — into any AI assistant. No API key. Works via stdio, Docker, or HTTP.
Paramus Chemistry INTENT
Makes hundreds of chemical calculations and AI model functions accessible to LLMs
SEOMCP
AI-native SEO service via MCP — gives Claude native access to keyword research, rank tracking, site audits, backlink analysis, and autonomous SEO agent workflows.
TengineAI
Run MCP tools in production without managing your own server — built-in retries, permissions, and observability.
HomeMCPBridge
Native macOS HomeKit integration for AI assistants via Model Context Protocol
Fast Mobile MCP
High-performance mobile automation architecture with a thin MCP gateway and dedicated Go workers for Android and iOS.
