"Best practices for using a library for a specific task" matching MCP servers:

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

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.

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

MCP server that brings live Australian racing and sports odds from 12 bookmaker/exchange sources into AI assistants, with per-price age data and tools for next races, best odds, results, and movers.

Provides access to Fantasy NBA Israel League statistics including team rankings, player stats, roster details, and shooting analytics for a specific private fantasy basketball league.

Enables Claude to look up Australian sports events and retrieve every bookmaker’s current decimal prices, the best available price, and no-vig fair odds for head-to-head, line, and total markets.

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

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 LLMs to accurately convert climbing grades across different rating systems using a data-driven approach.

Enables AI assistants to answer tennis tactical questions using shot-by-shot charted match data, producing game plans, serve and return tendencies, scouting reports, match forecasts, and explanations of why a match turned. Exposes read-only tools for player reports, head-to-head game plans, match breakdowns, and tactical leaderboards, each with confidence margins and links to full pages.

Enables reading and scoring Fleaflicker fantasy football leagues, including rosters, standings, matchups, boxscores, draft boards, and stat line scoring using league-specific rules, with no authentication required.

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.

MCP server that provides fantasy football draft tools including ranked boards, best available, player comparisons, sleeper/bust flags, and ADP market gaps using a calibrated projection model.

A Modular Command-line Program for fetching and filtering NFL transaction data, including player movements, injuries, disciplinary actions, and more from ProSportsTransactions.com.

Enables Claude to interact with Sleeper fantasy football leagues via MCP tools for roster, waiver, matchup, and transaction queries, plus a dashboard for daily reports, live scoring, and game-day alerts.

Live CS2 FACEIT data for Claude — query player stats, match history, head-to-head comparisons, recent form, per-map breakdowns, and full match scoreboards for any public FACEIT player using natural language.

An MCP server that analyzes upcoming weather at alpine peaks and trailheads worldwide, ranking the best windows for climbing and ascent using high-resolution forecast models.

Provides 28 MCP tools to query KBO baseball data, including player stats, pitch arsenal, zone charts, usage patterns, and trend reports using a SQLite database.

Exposes Zwift training history stored in a local SQLite database to MCP clients and a REST API, enabling queries for activities, power curves, race results, and training load.

Enables users to estimate football match probabilities using a Dixon-Coles model, compare them to de-vigged bookmaker odds, and identify value bets from Claude Desktop.