DiscGolfAPI vs Stathead MCP
A side-by-side look at the DiscGolfAPI and Stathead MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose DiscGolfAPI for sports work over a hosted endpoint; choose Stathead MCP for sports as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose DiscGolfAPI when
- You need dedicated capabilities in the Sports domain.
- You prefer a remote HTTP/SSE transport.
- Its auth model fits you: No auth required.
- You want tools like
search_courses, find_courses_near, get_course.
Choose Stathead MCP when
- You need dedicated capabilities in the Sports domain.
- You prefer a local stdio subprocess transport.
- You want tools like
get_metadata, get_player_season_stats, get_player_weekly_stats.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Sports | Sports |
| Quality signal | 77/100 · Great | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Remote HTTP/SSE | Local subprocess (stdio) |
| Auth | No auth required | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Verified | Community listing |
| GitHub stars | — | 3 |
| Directory activity | 6 views 3 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 4 | 55 |
| Full listing | View DiscGolfAPI | View Stathead MCP |
Tools & capabilities
DiscGolfAPI tools 4
search_coursesSearch for disc golf courses by name, city, country, region, hole count, or features.find_courses_nearFind disc golf courses within a specified radius (km) of given coordinates.get_courseRetrieve detailed information for a specific disc golf course by its unique ID or alias.get_recent_updatesDiscover recently added or updated disc golf courses with change type and timestamps.
Stathead MCP tools 55
get_metadataDescribe this server's capabilities: available tools, data sources, per-source season coverage, and valid enum values (positions, scoring formats, league sizes, ADP sources). Call this FIRST to scope a question correctly — it tells you what seasons/sources/formats are supported so you don't have to probe by trial and error. Takes no arguments.get_player_season_statsGet aggregated season totals for NFL players — offence, defence (IDP), kicking and punting. Returns rushing, passing, receiving, fantasy stats and 2-point conversions, and via `fields` every other counting column nflverse carries: defensive (def_tackles_solo, def_tackle_assists, def_tackles_for_loss, def_sacks, def_qb_hits, def_pass_defended, def_interceptions, def_fumbles_forced, def_tds, def_safeties), punting (pt_att, pt_yards, pt_net_yards, pt_inside_20, pt_long, pt_touchback) and kicking (fg_made/fg_att by distance band, pat_made/pat_att). Filter by position: QB/RB/WR/TE/K/P/FB, the nflverse defensive codes (DE, DT, LB, CB, SAF), or the IDP buckets DL (DE+DT+NT), LB and DB (CB+SAF+FS+SS). Sort by any stat column. Punting columns need a season pulled from nflverse's unified table — 2025 onward locally, any season when fetched live. Use this for player performance, fantasy points, rankings, comparisons. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_player_weekly_statsGet week-by-week stats — game logs — for one player or for a whole position in a season. Pass player_name for one player's log, or omit it and pass position (and optionally week_start/week_end or team) for every player at that position, which is how you get a weekly board. Covers offence, defence (IDP) and specialists: with `fields` you can project any raw nflverse weekly column, including def_tackles_solo, def_tackle_assists, def_sacks, def_qb_hits, def_pass_defended, def_interceptions, def_tackles_for_loss, def_tds, punting (pt_att, pt_yards, pt_net_yards, pt_inside_20) and returns (punt_returns, punt_return_yards, kickoff_returns, kickoff_return_yards). Positions accept QB/RB/WR/TE/FB/K/P, the nflverse defensive codes (DE, DT, LB, CB, SAF) and the IDP buckets DL/LB/DB. A whole position-week is a few hundred rows, so narrow with week_start/week_end or team, and raise limit deliberately. Use for game logs, weekly trends, consistency and boom/bust analysis, and week-by-week IDP scoring. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_gamesGet NFL game results and schedules. Includes the canonical nflverse game_id (e.g. 2024_04_BUF_BAL, handles neutral-site/relocated games correctly), scheduled kickoff (gameday = date, weekday, gametime = kickoff in US Eastern HH:MM), home/away/week, scores, spreads, totals, weather, surface. Use for team records, point totals, home/away splits, deriving day/time windows, bye weeks (a team absent from a week's games is on bye), or to enumerate game_ids to feed get_play_by_play. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_snap_countsGet offensive/defensive snap count percentages by player per week. Use for workload analysis, role changes, snap share trends. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_rookie_snap_shareRookie snap-share RAMP tracker — weekly offensive snap % for a season's rookie class, with a ramp signal (last-3-week avg − first-3-week avg) that surfaces mid-season role expansion a static depth chart misses (the classic late-bloomer pattern, e.g. a rookie RB climbing from 30% to 70% snaps). Identifies rookies from the roster (years_exp 0 / rookie or entry year = season). For an in-progress season this is a live leading indicator; for a completed season it's the role-trajectory record. Sort by ramp (biggest risers), latest, peak, or avg. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_combine_resultsGet NFL Combine athletic testing results. Includes 40-yard dash, bench press, vertical jump, broad jump, 3-cone drill, shuttle, height, weight, draft position. Use for athletic profile analysis, draft capital evaluation. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_draft_picksGet historical NFL draft picks with career outcomes. Includes round, pick, team, college, career approximate value (car_av), Pro Bowls, All-Pro selections, Hall of Fame status. Note: career columns (car_av, pro_bowls, etc.) are cumulative and are blank/low for recent draftees who are still active — they populate as careers progress. Use for draft analysis, career success by pick, team drafting history. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_rookie_classOne-call rookie-class join: NFL draft picks for a draft year + combine testing + that player's rookie-season (same year) production — so you don't have to join draft, combine, and stats by hand. Skill positions (QB/RB/WR/TE) by default. Each row carries pfr_id for joining to other tools. Great for prospect/dynasty evaluation and hit-rate analysis. Anti-pattern: do not multiply marginal factors (athleticism × age × draft slot) into a "P(Hit)" — the factors are correlated and the product is over-confident; use as ordinal ranking or compare similar-player (joint) comps instead. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_injuriesGet weekly NFL injury reports (nflverse, 2009+). Per player-week: gsis_id (joinable to get_play_by_play / get_player_crosswalk), primary + secondary injury, practice participation (primary/secondary injury + practice_status), and final game report_status (Out/Doubtful/Questionable). Use for injury impact analysis, weekly availability, and attaching injury status to a roster. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_advanced_statsGet PFR advanced stats: passing (pressure rate, drop rate, bad throws), rushing (yards before/after contact, broken tackles), receiving (drops, YAC). Use for efficiency and process metrics beyond box score. See also: get_metadata for season coverage, valid enums, and analytic caveats.get_play_by_playGet play-by-play data with EPA, WPA, win probability, air yards, YAC, and stable player IDs (passer/rusher/receiver_player_id = nflverse gsis_id, joinable to get_player_crosswalk). Default view is lean; pass `fields` to project any of these slim columns — including kicker/defense/special-teams columns for K & DST fantasy scoring: kicker_player_id, kicker_player_name, kick_distance, extra_point_result; sack, interception, fumble, fumble_lost, fumble_recovery_1_team, safety; td_player_id, td_team, return_touchdown (separates defensive/ST TDs from offensive); two_point_attempt, two_point_conv_result; and kick/punt return columns: return_yards, return_team, kickoff_returner_player_id, kickoff_returner_player_name, punt_returner_player_id, punt_returner_player_name, fair_catch (note: yards_gained is 0 on return plays — use return_yards); committed-turnover + recovery attribution: interception (+ passer_player_id = who threw it), fumble_lost (+ fumbled_1_player_id/_name/fumbled_1_team = who lost it, fumble_recovery_1_player_id/_name = who recovered, forced_fumble_player_1/2_player_id = who forced it); per-defender IDP attribution (project via fields): solo_tackle_1/2_player_id, assist_tackle_1..4_player_id, tackle_for_loss_1/2_player_id, sack_player_id, half_sack_1/2_player_id, qb_hit_1/2_player_id, interception_player_id, pass_defense_1/2_player_id (all gsis, crosswalkable; defensive/ST TD scorer is td_player_id with td_team=defteam); and real (wall-clock) time: game_date, start_time (kickoff), time_of_day (UTC time the play was run — vs the game-clock `time` field; note nflverse populates it for most recent-season plays but it can be sparse/older-season gaps). Use for situational analysis (red zone, 3rd down, 2-minute drill), play type breakdowns, EPA-based efficiency, scoring K/DST, or pulling a complete game with game_id. WARNING: Large dataset — always filter by game_id, player, team, or situation. To pull an ENTIRE WEEK set limit ~3000 (a week is ~2400 plays) with week=N; to pull a WHOLE SEASON set a high limit (e.g. limit=50000, season ~43k plays) — for these large pulls always use output_format=jsonl or csv (optionally + fields) to keep the payload compact. You can also page with offset (the header reports the next offset and the total). When projecting with `fields`, include game_id/play_id/posteam/defteam yourself if you need them for joins. See also: get_metadata for season coverage, valid enums, and analytic caveats.- +43 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
DiscGolfAPI
{
"mcpServers": {
"discgolfapi": {
"url": "https://io.discgolfapi.com/mcp"
}
}
}
Stathead MCP
{
"mcpServers": {
"stathead-mcp": {
"command": "npx",
"args": [
"-y",
"stathead-mcp"
]
}
}
}
Frequently asked questions
DiscGolfAPI is categorized under Sports and uses a remote HTTP/SSE transport. Stathead MCP belongs to Sports and uses a local stdio subprocess. Pick DiscGolfAPI for sports work and Stathead MCP for sports.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
DiscGolfAPI is listed as free. Auth: no auth required. Stathead MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add discgolfapi and stathead-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, DiscGolfAPI has a quality signal of 77/100 (Great) with 6 views, 3 installs and 0 GitHub stars. Stathead MCP has 64/100 (Good) with 1 views, 0 installs and 3 GitHub stars.