"Connecting Firebase to a data source or application" matching MCP servers:

Enables local read-only access to TheRundown Product API data including sports, affiliates, market definitions, events, futures, and open main lines using your own API key.

Enables searching golf courses for free and retrieving premium data such as scorecards, GPS mappings, course details, and green slope images via a credit-based API with explicit spend confirmation.

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.

Provides seamless access to iRacing's racing simulation data, enabling AI assistants to retrieve driver profiles, career statistics, and team information. It features automatic authentication and tools for real-time driver lookups and season performance analysis.

Access football (soccer) data including competitions, matches, standings, and team details via the Football-Data.org API.

Provides football analytics tools including player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more for 10 leagues.

Enables AI agents to access comprehensive sports data including football, basketball, American football, and hockey leagues via 11 tools, with no API key required.

Provides read-only access to sports data, odds intelligence, and historical stats via 10 MCP tools, with fast response times through Redis caching.

Enables MCP clients to query documented Sportmicro football endpoints for players, teams, matches, player statistics, and weekly/season projections through narrow, read-only, validated 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.

An open-source MCP server that connects to the SoccerDataAPI to deliver up-to-date football match information via natural language interactions.

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.

Provides live football data through MCP tools, enabling users to fetch today's matches and top scorers for competitions like the Premier League or World Cup.

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

Gives any MCP client local access to Garmin Connect sleep and nap data, recovery and Body Battery, training readiness and load, running tolerance, VO2 Max, race predictions, gear mileage and running summaries. It runs over stdio or Streamable HTTP and includes a credential-free demo mode with fictional sample data.

Enables AI agents to query real-time and historical Formula 1 data, including Grand Prix meetings, sessions (races, qualifying, practice), drivers, and lap times or telemetry, with support for filtering by year, country, session, and driver. Can be used via the Pipeworx gateway or as a local stdio server.

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.

Enables AI assistants like Claude to read a single user's own Strava account through its API: profile and totals, activities with laps, splits, zones and per-second streams, plus segments, routes, gear and clubs. It is strictly read-only, using the user's own Strava API application and OAuth tokens stored locally, and returns model-friendly, context-sized data.

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