"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

Fantasy Premier League stats and press coverage for AI agents: read-only SQL over FPL player, fixture and gameweek data, plus semantic search over BBC Sport and Guardian articles and FPL injury news. Bring your own PostgreSQL and Pinecone, with bundled ingestion jobs.

Enables AI agents to safely interact with golf course operations by providing real-time inventory, booking rules, pricing policies, and a self-learning memory system.

Provides real-time access to League of Legends esports data including live matches, schedules, leagues, event details, and VODs through a standardized interface.

Standalone Model Context Protocol server for PropProfessor, plus a small query CLI for local analysis.

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

A Model Context Protocol server for TrainingPeaks with an analytics focus — enabling real-time querying of training data, performance trends, CTL/ATL/TSB analysis, and training load optimization through Claude Desktop.

A Model Context Protocol server that gives AI assistants real-time access to the MCSR Ranked competitive Minecraft speedrunning API, enabling plain-language queries about players, matches, stats, and more.

A lightweight Garmin Model Context Protocol server with 12 curated endpoints for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal data from Garmin Connect.

Enables AI agents to query live sports betting odds, best prices, arbitrage, +EV bets, and middles directly through Model Context Protocol tools.

Live ski & snow data for AI agents: 14-day multi-model forecasts, powder rankings, resort guides, webcams, ski-pass intelligence, and avalanche/road safety across 500+ resorts. Hosted streamable-HTTP — no install, no auth.

A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.

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.

Integrates iRacing with the Model Context Protocol to retrieve profile statistics and iRating charts for any category.

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 Formula One data and statistics through a Model Context Protocol interface, allowing users to access race calendars, session results, driver statistics, telemetry data, and championship standings.

A Model Context Protocol server that provides access to Fantasy Premier League data, allowing users to compare players, find team information, view gameweek data, and get FPL-related advice through Claude for Desktop and other MCP-compatible clients.

Provides AI agents with live, grounded sports data including model probabilities, track records, and European soccer and tennis arbitrage opportunities, so they answer from real numbers instead of stale guesses.

Provides comprehensive NBA statistics via Model Context Protocol, enabling queries for player stats, game scores, team info, and advanced analytics through natural language.

Provides natural language access to IPL cricket match data, allowing users to query player statistics, team performances, and match results. It utilizes a SQLite backend and Cricsheet data to deliver detailed cricket analytics through the Model Context Protocol.

A Model Context Protocol server for the Sportmonks Football API v3, providing over 150 tools to access football data including fixtures, teams, players, odds, predictions, and more.