Chess.com API

Chess

Engage in challenging chess matches against language models using an interactive platform featuring advanced tools for board display, executing moves, starting games, and analyzing positions based on PGN notation. Enjoy a dynamic chess experience like never before!

College Football Data

Unlock valuable insights with seamless integration with the College Football Data API, enabling intuitive search capabilities for game outcomes, team standings, player performance, ratings, and in-depth analytics.

Twitch

Easily connect to the Twitch API for access to a wide range of channel information, streaming specifics, gaming data, user profiles, clips, chat configurations, and video feedback. Ideal for developing tools and analytics focused on Twitch functionality.

Chess

Enhance your chess applications and research projects with seamless integration with chess engines and libraries. Access advanced game analysis, move generation, and position evaluation capabilities through the Model Context Protocol (MCP).

Lichess

Enhance your gaming experience on Lichess by seamlessly integrating with the Model Context Protocol (MCP) for intuitive gameplay, analysis, and engaging tournament involvement using its advanced API capabilities.

Chess

Experience interactive chess gameplay and automated analysis through seamless integration with Spring AI and leading chess libraries. Enhance your AI-assisted chess applications with this cutting-edge Model Context Protocol (MCP) solution.

Steam

Unlock insights into user behavior and gaming preferences by seamlessly tapping into the power of the Steam Web API. Access valuable user data, game details, and a range of Steam-related features to enhance your app with personalized recommendations, deep user analytics, and seamless integration of Steam profiles.

NBA Stats

Access up-to-the-minute NBA game details such as scores, player performance metrics, and live action updates using the nba_api tool. Stay updated with the latest basketball data beyond what is available in traditional training datasets.