"How to extract and analyze data from a MongoDB database" 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.

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 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.

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.

MCP server that gives Claude programmatic access to a local En Croissant chess opening trainer, enabling conversational opening prep by reading its SQLite database, PGN files, and Lichess API. It supports repertoire review, due cards, and opponent statistics directly from chat.

Provides AI-powered sports betting intelligence including live odds, injury reports, and documented picks for NBA, NHL, and NCAAB. It enables AI agents to analyze line movements, win rates, and betting edges using real-time data from sportsbettingaianalyzer.com.

Enables AI assistants to analyze Fantasy Premier League data, providing tools for player search, fixture analysis, manager comparisons, and strategy prompts for transfer planning and lineup selection.

Provides soccer match predictions and league statistics using xG data and Poisson distribution models. It enables users to forecast outcomes, analyze team performance, and view league tables across major European football leagues.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

Enables AI assistants to access sports betting odds data from 265+ bookmakers across 34 sports, including events, odds, historical data, arbitrage, and value bets.

Enables AI assistants to directly access and analyze Strava activity data, including runs, rides, and swims, through natural language queries.

Analyze iGPSport cycling data with natural language, computing derived training metrics (NP, IF, TSS, CTL, ATL, TSB) locally via MCP.