Stathead MCP vs MCP Server Chart
A side-by-side look at the Stathead MCP and MCP Server Chart MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Stathead MCP for sports work as a local process; choose MCP Server Chart for data visualization as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
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.
Choose MCP Server Chart when
- You need dedicated capabilities in the Data Visualization domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
generate_area_chart, generate_bar_chart, generate_boxplot_chart.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Sports | Data Visualization |
| Quality signal | 64/100 · Good | 71/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 3 | 4,402 |
| Directory activity | 1 views 0 installs 0 upvotes | 10 views 0 installs 0 upvotes |
| Tools | 55 | 27 |
| Full listing | View Stathead MCP | View MCP Server Chart |
Tools & capabilities
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
MCP Server Chart tools 27
generate_area_chartGenerate a area chart to show data trends under continuous independent variables and observe the overall data trend, such as, displacement = velocity (average or instantaneous) × time: s = v × t. If the x-axis is time (t) and the y-axis is velocity (v) at each moment, an area chart allows you to observe the trend of velocity over time and infer the distance traveled by the area's size.generate_bar_chartGenerate a horizontal bar chart to show data for numerical comparisons among different categories, such as, comparing categorical data and for horizontal comparisons.generate_boxplot_chartGenerate a boxplot chart to show data for statistical summaries among different categories, such as, comparing the distribution of data points across categories.generate_column_chartGenerate a column chart, which are best for comparing categorical data, such as, when values are close, column charts are preferable because our eyes are better at judging height than other visual elements like area or angles.generate_district_mapGenerates regional distribution maps, which are usually used to show the administrative divisions and coverage of a dataset. It is not suitable for showing the distribution of specific locations, such as urban administrative divisions, GDP distribution maps of provinces and cities across the country, etc. This tool is limited to generating data maps within China.generate_dual_axes_chartGenerate a dual axes chart which is a combination chart that integrates two different chart types, typically combining a bar chart with a line chart to display both the trend and comparison of data, such as, the trend of sales and profit over time.generate_fishbone_diagramGenerate a fishbone diagram chart to uses a fish skeleton, like structure to display the causes or effects of a core problem, with the problem as the fish head and the causes/effects as the fish bones. It suits problems that can be split into multiple related factors.generate_flow_diagramGenerate a flow diagram chart to show the steps and decision points of a process or system, such as, scenarios requiring linear process presentation.generate_funnel_chartGenerate a funnel chart to visualize the progressive reduction of data as it passes through stages, such as, the conversion rates of users from visiting a website to completing a purchase.generate_histogram_chartGenerate a histogram chart to show the frequency of data points within a certain range. It can observe data distribution, such as, normal and skewed distributions, and identify data concentration areas and extreme points.generate_line_chartGenerate a line chart to show trends over time, such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016.generate_liquid_chartGenerate a liquid chart to visualize a single value as a percentage, such as, the current occupancy rate of a reservoir or the completion percentage of a project.- +15 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.
Stathead MCP
{
"mcpServers": {
"stathead-mcp": {
"command": "npx",
"args": [
"-y",
"stathead-mcp"
]
}
}
}
MCP Server Chart
{
"mcpServers": {
"antv-mcp-server-chart": {
"command": "npx",
"args": [
"-y",
"@antv/mcp-server-chart"
]
}
}
}
Frequently asked questions
Stathead MCP is categorized under Sports and uses a local stdio subprocess. MCP Server Chart belongs to Data Visualization and uses a local stdio subprocess. Pick Stathead MCP for sports work and MCP Server Chart for data visualization.
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.
Stathead MCP has no declared pricing — check the project's own site. MCP Server Chart is listed as free. Auth: no auth required. 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 stathead-mcp and antv-mcp-server-chart as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Stathead MCP has a quality signal of 64/100 (Good) with 1 views, 0 installs and 3 GitHub stars. MCP Server Chart has 71/100 (Great) with 10 views, 0 installs and 4,402 GitHub stars.