"Guide for Updating Code Version from Java 17 to 18 or Python 2 to 3" matching MCP servers:

Provides verified game rules, official links, and FAQ for the 17-0 NFL roster strategy game to MCP-compatible AI clients.

Exposes the canonical 17-0 knowledge surface including game rules, roster constraints, and entry points for the NFL roster strategy game to MCP-compatible AI clients.

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.

FastMCP server for Dota 2 match analysis using replay files and OpenDota API, with built-in coaching instructions for LLMs.

Enables MCP clients to fetch live football odds and team form, and flag matches where the market price diverges from a simple form-based estimate.

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.

A read-only MCP server providing calibrated Dota 2 and Deadlock win-rate predictions and hero counters via batru.gg's live API.

Read-only MCP server for sourced Dota 2 tournament, team, player, schedule, and result data from Liquipedia, with revision-level metadata and caching.

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

29 MCP tools for IPL 2026, IPL historical (18 seasons), and Major League Cricket. Free, no API key.

Enables LLMs and agents to query Dota 2 matches, players, heroes, teams, and pro scene data through the OpenDota API, with numeric IDs resolved to localized names and readable labels.

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.

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

Provides access to official MLB statistics via a keyless API, enabling AI agents to query MLB data through natural language or direct tools.

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.

Enables AI agents to query sports data including teams, players, events, and standings from TheSportsDB through natural language or direct tool calls.

CLI and MCP server for EdgeFinder sports analysis. Get AI-powered NFL, NBA, and MLB betting recommendations, player stats, odds, schedules, and Polymarket portfolio tracking from your terminal or AI agent.