NBA Odds MCP Server
@nikhilkichili
About NBA Odds MCP Server
Advanced NBA odds tracking, betting analysis, and trivia MCP server for Claude Desktop with line movement detection and AI/ML game simulations
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"nba-analytics-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tools
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Overview
What is NBA Odds MCP Server?
NBA Odds MCP Server is a Model Context Protocol (MCP) server that provides NBA basketball odds data from The Odds API. It enables large language models (LLMs) like Claude to access real-time NBA betting odds, game schedules, championship odds, and simulation tools. It's intended for users of MCP-compatible clients who want NBA odds and analysis.
How to use NBA Odds MCP Server?
Requires Python 3.10+, a virtual environment, and dependencies (mcp[cli], httpx). Run python nba_odds_server.py after activation, then configure your MCP client (e.g., Claude Desktop) by adding the server command and args to claude_desktop_config.json. Ask natural language questions like "What are the current odds for the NBA Championship?" to get odds data.
Key features of NBA Odds MCP Server
- Provides current NBA games with betting odds (h2h, spreads, totals)
- Returns NBA Championship winner odds and team-specific schedules
- Includes game simulation tools for AI/ML-based predictions
- Offers betting analysis (ATS performance, odds movement, recommendations)
- Supports NBA trivia quiz with multiple categories and difficulty levels
- Generates visual line‑movement charts using Matplotlib
Use cases of NBA Odds MCP Server
- Ask an LLM for real‑time NBA game odds and compare bookmakers
- Simulate NBA games or championship outcomes for entertainment or trend analysis
- Analyze historical odds data (line movements, sharp money) for betting research
- Practice NBA knowledge through interactive trivia quizzes
- Track championship odds trends and generate comparison charts
FAQ from NBA Odds MCP Server
What data does NBA Odds MCP Server provide?
It provides current NBA game odds, championship winner odds, team schedules, and basic league info. All data comes from The Odds API; the server handles authentication and formatting.
What are the runtime requirements?
Python 3.10 or higher, a virtual environment, and the packages mcp[cli] and httpx. For visualizations, Matplotlib, NumPy, and Pillow are also required.
Where is historical odds data stored?
Data is stored locally in a SQLite database. Championship odds and game odds are automatically saved for trend analysis. Charts are saved to a charts folder and returned as base64 images.
How does the server communicate with clients?
It uses the Model Context Protocol (MCP) over stdio transport. Configure the server command in your MCP client’s configuration file (e.g., claude_desktop_config.json) to connect.
Do I need my own API key?
No. The Odds API key is included in the server configuration. The server uses the key to fetch data from The Odds API endpoints.
Frequently asked questions
What data does NBA Odds MCP Server provide?
It provides current NBA game odds, championship winner odds, team schedules, and basic league info. All data comes from The Odds API; the server handles authentication and formatting.
What are the runtime requirements?
Python 3.10 or higher, a virtual environment, and the packages `mcp[cli]` and `httpx`. For visualizations, Matplotlib, NumPy, and Pillow are also required.
Where is historical odds data stored?
Data is stored locally in a SQLite database. Championship odds and game odds are automatically saved for trend analysis. Charts are saved to a `charts` folder and returned as base64 images.
How does the server communicate with clients?
It uses the Model Context Protocol (MCP) over stdio transport. Configure the server command in your MCP client’s configuration file (e.g., `claude_desktop_config.json`) to connect.
Do I need my own API key?
No. The Odds API key is included in the server configuration. The server uses the key to fetch data from The Odds API endpoints.
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