"A platform to consolidate all messaging apps in one place" 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.

A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.

Provides Formula One data and statistics through a Model Context Protocol interface, allowing users to access race calendars, session results, driver statistics, telemetry data, and championship standings.

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.

Live sports betting player props MCP server covering NBA, MLB, NFL, NHL, NCAA, and soccer. Unified from real sportsbooks into one REST API and a real MCP server (Streamable HTTP). Free tier, no card required.

Enables AI tools to query sports tournaments, leaderboards, predictions, and match stats from the Tulidu Sport platform.

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.

MCP server for kicktipp.com that enables AI assistants to view match data, leaderboards, and place bets through natural language.

Provides read-only access to an Abler account's profile, groups, and sports schedules through MCP tools, including per-child schedule reports and individual event lookups. Uses a portable, reusable session credential so it can run headlessly on a remote machine after a one-time browser sign-in.

Read-only MCP server for the PlayMetrics youth-sports club management platform, enabling AI agents to query clubs, teams, players, schedules, registrations, and payments.

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.

An MCP server that enables natural language querying of over 10 million ball-by-ball cricket deliveries stored in a local DuckDB database. It provides 26 tools for analyzing player matchups, situational stats, and historical records across all major cricket formats and tournaments.

Exposes court-availability data as a read-only panel rendered in MCP hosts (Claude Desktop, VS Code, test host) via a UI resource.

An open-source MCP server that turns any AI assistant into a football data analytics and scouting platform, enabling natural language queries over 40+ stats, 20+ leagues, and 10,000+ players.

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.

MCP server that connects AI assistants to the Statos football analytics platform, enabling natural language queries for match predictions, betting picks, league information, and admin market-suppression controls.

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.

A read-only MCP server that provides access to the public Basketball Vlaanderen (VBL) API, enabling users to query clubs, teams, matches, standings, and more.

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.

A local MCP server that gives Claude (or any MCP-compatible AI client) access to Formula 1 race data. Load any session from 2018 onwards, ask questions in natural language, and get answers backed by real telemetry, timing, and strategy data.