"How to integrate an information system with DeepSeek" matching MCP servers:

Enables AI agents to interact with ActiveNet OpenAPI services for managing organizations, activities, customers, facilities, and more.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.

Enables access to MLB Stats API data including game schedules, results, team information, and player lookups with fuzzy matching support through the Model Context Protocol.

Provides access to Chess.com player data, game records, and public information through standardized MCP interfaces, allowing AI assistants to search and analyze chess information.

Enables fetching football fixtures, match details, league tables, and squad information from the matchday app through natural language.

Provides access to the Intervals.icu API for interacting with training data, activities, events, and wellness information.

Enables fetching sportsbook odds, live scores, and event information across 70+ books and 30+ leagues, with tools to list sports, get scores, and discover events.

Enables interaction with Formula 1 data through LLM interfaces like Claude. Provides access to F1 information including circuits, constructors, drivers, grand prix, manufacturers, races, and seasons.

Wraps CricAPI to provide live cricket data, enabling AI agents to query cricket information through natural language or direct tool calls.

Provides comprehensive access to ESPN's sports APIs for live scores, team information, news, and statistics across NFL, NBA, MLB, NHL, college sports, and major soccer leagues with advanced filtering and real-time updates.

An open-source MCP server that connects to the SoccerDataAPI to deliver up-to-date football match information via natural language interactions.

Enables interaction with the wger Workout Manager database to retrieve exercises, muscles, and equipment information.

A server that integrates Sleeper fantasy sports data with Goose AI through the Machine Context Protocol (MCP), providing structured access to fantasy league information.

Connects Claude to Cartola FC, enabling queries about matches, player scores, and market information through natural language.

Multi-agent parlay optimization system using CrewAI to analyze games, evaluate props, and construct optimal parlay combinations.

Enables management of sports video metadata with PostgreSQL backend, supporting CRUD operations, advanced search, and tracking of game information including teams, scores, player statistics, and match details.

This Model Context Protocol server provides access to the Sleeper Fantasy Football API, enabling agents to fetch data about users, leagues, drafts, rosters, matchups, and player information without requiring an API key.

Manages sports video metadata with CRUD operations for game information, teams, scores, and statistics. Enables advanced search filtering by game type, teams, league, season, and date ranges through PostgreSQL integration.