developer-toolsanalytics-data

NBA

obinopaul

by obinopaul

Access real-time NBA stats, including LeBron James statistics, Luka Doncic and Anthony Edwards stats, with live updates

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.

github stars

2

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Real-time live game dataOfficial NBA API integration10+ specialized NBA data tools

best for

  • / Sports app developers building NBA features
  • / Data analysts studying basketball statistics
  • / Fantasy basketball applications
  • / Sports betting and analysis platforms

capabilities

  • / 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

what it does

Provides access to comprehensive NBA data including live game scores, player stats, team standings, and historical information through the NBA's official API.

about

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

MIT

NBA is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Access real-time NBA stats, including LeBron James statistics, Luka Doncic and Anthony Edwards stats, with live updates

TL;DR: Provides access to comprehensive NBA data including live game scores, player stats, team standings, and historical information through the NBA's official API.

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

  • Sports app developers building NBA features
  • Data analysts studying basketball statistics
  • Fantasy basketball applications
  • Sports betting and analysis platforms

Highlights

  • Real-time live game data
  • Official NBA API integration
  • 10+ specialized NBA data tools

FAQ

What is the NBA MCP server?
NBA is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for NBA?
This profile displays 36 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.736 reviews
  • Shikha Mishra· Dec 24, 2024

    NBA has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Chinedu Chawla· Dec 20, 2024

    Strong directory entry: NBA surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Emma Verma· Dec 4, 2024

    Useful MCP listing: NBA is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Yuki Rao· Nov 23, 2024

    According to our notes, NBA benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Ama Mensah· Nov 11, 2024

    I recommend NBA for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Emma Dixit· Nov 3, 2024

    NBA has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Evelyn Abbas· Oct 22, 2024

    We evaluated NBA against two servers with overlapping tools; this profile had the clearer scope statement.

  • James Perez· Oct 14, 2024

    We wired NBA into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Chinedu Abebe· Oct 2, 2024

    NBA reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Layla Ndlovu· Sep 21, 2024

    Strong directory entry: NBA surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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