NFL Data MCP Server
Related Servers
Alternatives to NFL Data MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceProvides verified NFL stats (2016–2025) and Sleeper league context through an MCP server, with tools for querying metrics, comparing entities, verifying claims, and accessing league data.MIT
- AlicenseNot gradedqualityDmaintenanceProvides comprehensive NBA player statistics from basketball-reference.com, delivering detailed stats including career summaries, season comparisons, advanced metrics, and shooting analytics.3MIT
- FlicenseAqualityDmaintenanceEnables natural language interaction with Sleeper Fantasy Football API data, allowing queries about leagues, players, matchups, draft results, and trade analysis.1324-
- FlicenseAqualityDmaintenanceProvides access to live NHL game data, player and team statistics, standings, schedules, playoff brackets, and historical comparisons through natural language queries using the official NHL API.11-
- AlicenseNot gradedqualityCmaintenanceAn MCP server that provides access to over 12 years of NFL play-by-play data through a local DuckDB database. It enables users to query player performance, team statistics, and situational efficiency metrics like EPA and WPA using natural language.7MIT
- AlicenseNot gradedqualityDmaintenanceProvides 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.MIT
TDQS
Scored across 4 tools
Each tool targets a distinct purpose: getting a player's stats, comparing players, retrieving position leaders, and searching players by name. There's slight overlap between get_player_stats and compare_players since both retrieve player statistics, but the former is single-player while the latter is multi-player, making them mostly distinguishable.
All tools follow a consistent verb_noun pattern: get_player_stats, compare_players, get_position_leaders, search_players. Each uses a clear action verb (get, compare, search) followed by the object (player_stats, players, position_leaders, players). This is highly predictable and consistent.
With 4 tools, the count is well within the appropriate range for a focused data retrieval server. Each tool services a distinct query pattern (individual lookups, comparisons, positional rankings, and searching). The count feels slightly lean but reasonable for a data-only server with no write operations.
The set covers core statistical queries: individual stats, comparison, position rankings, and discovery. However, there are notable gaps such as team-level stats, game-level data, week-by-week breakdowns, and season/league overviews that a comprehensive NFL data server might be expected to provide. An agent could often work around these gaps, so they're moderate rather than severe.