"How to fetch or scrape data from a website for use in training an LLM" matching MCP servers:

Provides comprehensive access to Strava API for marathon training and race analysis, enabling language models to query athlete data, analyze training patterns, track performance metrics, monitor heart rate zones, and detect injury risks.

Running-first MCP server for COROS that allows authoring, editing, and scheduling running workouts, plus accessing sleep, HRV, training load, and activity exports.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP chess runtime that lets LLMs play, analyze, and adapt strength by exposing Stockfish, human move likelihood (Maia3), and Lichess statistics, with the LLM handling strategy and the server handling computation.

Enables searching golf courses for free and retrieving premium data such as scorecards, GPS mappings, course details, and green slope images via a credit-based API with explicit spend confirmation.

Connect Claude to XERT cycling analytics - access fitness signature (FTP, LTP, HIE), training load, workouts, and activities.

Provides seamless access to iRacing's racing simulation data, enabling AI assistants to retrieve driver profiles, career statistics, and team information. It features automatic authentication and tools for real-time driver lookups and season performance analysis.

Access football (soccer) data including competitions, matches, standings, and team details via the Football-Data.org API.

Provides football analytics tools including player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more for 10 leagues.

Enables AI agents to access comprehensive sports data including football, basketball, American football, and hockey leagues via 11 tools, with no API key required.

MCP server for TrainingPeaks that reads workouts, fitness metrics (CTL/ATL/TSB), and health data, and creates/updates/deletes planned workouts. Enables AI-powered training plan management and automated adjustment based on performance, fatigue, and injury.

Provides read-only access to sports data, odds intelligence, and historical stats via 10 MCP tools, with fast response times through Redis caching.

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.

Enables fast real-time web search and access to premium data from trusted sources including news, financial markets, sports, and more. Supports AI agents with live data and curated content from various domains.

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

An MCP server that lets Claude plan cycling training in intervals.icu, upload workouts to the calendar, and review planned versus actual outcomes, fitness trends, and power curves.

Analyzes chess positions via Stockfish, returning best moves and evaluations from FEN or PGN input.

Four utilities in one server: PDF text, ruled tables and OCR from a URL as pages, documents or RAG chunks; YouTube thumbnail URLs and files with per-size availability; sports scores, schedules and standings across 33 leagues; and ATP/WTA tennis with per-set scores and draws.

Tells you when your favourite football teams play and where to watch in Denmark, using data from TheSportsDB.com and built-in Danish broadcast hints.