"A guide on utilizing Python for solving numerical problems using internet resources" matching MCP servers:

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 deterministic surf-window recommendations and explanations based on stored decisions, enabling safe surf planning through tool-backed evidence.

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

Provides access to live NHL game data, team and player statistics, standings, schedules, playoff information, and head-to-head comparisons through natural language queries using official NHL APIs.

Enables MCP clients to discover tournaments, inspect events, entrants, sets, standings, and streams for any game on start.gg using natural language.

Connects Claude to Lichess for playing chess games, analyzing positions with Stockfish cloud evaluation, and solving puzzles. Supports real-time gameplay including moves, challenges, draw offers, and accessing user profiles and game history.

Python MCP server that provides comprehensive access to MLB statistics and baseball data through a FastAPI-based interface. Acts as a bridge between AI applications and MLB data sources, enabling seamless integration of baseball statistics, game information, player data, and more.

Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.

A Python MCP server providing 11 tools for querying KenPom basketball analytics, including efficiency ratings, game predictions, four factors, and more through Claude.

A minimal Python MCP server that provides surf forecasts for a single Surfline spot. It fetches both conditions and rating data through the get_surf_forecast tool.

A Python-based MCP server that extracts football match data from multiple global sources like ESPN and BBC Sport using intelligent web scraping. It enables AI assistants to retrieve scheduled matches, real-time scores, and broadcasting details with advanced filtering for high-profile games.

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.

Answers lineup, trade, waiver, and playoff-odds questions by running deterministic Python analysis and returning conclusions, not raw data.

Automates tennis court bookings on San Francisco Recreation websites using browser automation, with tools to check availability, initiate booking with SMS verification, and complete bookings.

An MCP server that answers football questions with interactive widgets, centered on the 2026 FIFA World Cup using SofaScore API data.

Enables Claude to securely read Sleeper fantasy football league data over the internet via the public API, supporting access from both Claude Desktop and mobile devices.

Provides surf forecast data including swell height, period, direction, and wind conditions for any location worldwide using the Open-Meteo Marine API. It also includes tools to find the best day to surf and integrates with MCP clients via a Python server.

MCP server for RapidOddsAPI that provides bookmaker odds, live scores, arbitrage and value bets to AI assistants. It supports querying sports, odds, results, and betting opportunities with credit-based usage.

Provides access to the Statbotics API for FIRST Robotics Competition statistical data and predictions. Enables AI assistants and other MCP clients to retrieve FRC team EPA ratings, event predictions, and match analytics.

Enables querying table tennis ratings, players, tournaments, and halls from rttf.ru, with respect for robots.txt restrictions.