"A server to build a knowledge base of Node.js packages with RAG search functionality" matching MCP servers:

Enables natural language querying of a football knowledge graph via Neo4j, generating Cypher queries and answers using LLMs, and also provides tools to build the graph from text.

MCP server for NFL fantasy football retrieval, providing access to NFL stats and Sleeper league data through retrieval-oriented tools.

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

Enables read-only search and lookup of US youth sports clubs and local sports stores, including registration windows, fees, tryouts, contacts, addresses, and brands, plus link generation for claiming or correcting listings.

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.

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.

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.

Enables AI agents to connect to Fantopy Arena, browse and enter fantasy football contests, build validated lineups, and claim payouts on Solana.

A physics-aware inline skating combo generator that models moves as state transitions to ensure sequences are executable and flow naturally. It allows users to generate custom skating routines and browse a catalog of wizard-style tricks.

Enables Claude to explore a Brazilian Jiu-Jitsu knowledge graph, searching positions, transitions, submissions, systems and principles, and retrieving detailed routes, execution steps, counters and defensive options.

Enables Claude, ChatGPT and other MCP clients to look up members, their memberships and credentials, events and event bookings, and clubs and other organisations in a sports membership platform, and, when writes are enabled, to change the dates of a member's membership.

Enables natural-language querying of a local DuckDB warehouse of NFL play-by-play data, converting questions into SQL and returning results.

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.

Converts Claude Desktop into a sports content production studio, enabling search of football transfer tweets and generation of complete videos with virtual presenters.

Connect AI agents to OP.GG Esports data and retrieve upcoming League of Legends match schedules effortlessly. Access structured match information through a standardized interface, enhancing your AI's capabilities with real-time esports data.

A unified MCP server that combines The Odds API and SportMonks Football API v3 to provide 28 tools for sports data like odds, scores, fixtures, standings, and predictions, enabling Claude to interact with a wide range of sports information.

Connects a user's F1Laps account to ChatGPT, Claude, and other compatible assistants, enabling read-only queries and analysis of saved F1 game laps, sessions, setups, and progress statistics.

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 interaction with the CopaMind platform via MCP, exposing read-only and write tools for querying match predictions, Monte Carlo simulations, team rankings, and RAG-based explanations, all while maintaining full traceability and reproducibility.

Enables natural-language querying of historical NBA game data from a read-only SQLite database.