io.github.Ninjabeam20/sportiq-mcp

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Au dernier audit MCP Hub, le serveur MCP « io.github.Ninjabeam20/sportiq-mcp » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.

Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 44 outils

• cricket_build_dream11_team≈ 662 tokens

  Recommend an optimal fantasy XI + captain + vice-captain for one fixture. Args: match_id: CricAPI match identifier; resolves team_a/team_b/venue automatically. team_a: First team code/name (e.g. ``MI``). Required if match_id is absent. team_b: Second team code/name (e.g. ``CSK``). Required if match_id is absent. venue: Venue key/name (e.g. ``wankhede``). Required if match_id is absent. strategy: ``"balanced"`` only in Phase 2; future variants reserved. Returns: data.players: 11 picked players with name/role/credits/team/projected_points. data.captain: name of the chosen captain. data.vice_captain: name of the chosen VC. data.total_credits: sum of credits used (<= 100). data.total_projected_points: fantasy points including C x2 and VC x1.5 boosts. meta.estimated: true — projections are model output, not a fantasy oracle. Example: cricket_build_dream11_team(team_a="MI", team_b="CSK", venue="wankhede") cricket_build_dream11_team(match_id="abc123")

  Paramètres, retour & exemple (5)

  Paramètres

  • venue · ? · optionnel
    Venue key/name (e.g. ``wankhede``). Required if match_id is absent.
  • team_a · ? · optionnel
    First team code/name (e.g. ``MI``). Required if match_id is absent.
  • team_b · ? · optionnel
    Second team code/name (e.g. ``CSK``). Required if match_id is absent.
  • match_id · ? · optionnel
    CricAPI match identifier; resolves team_a/team_b/venue automatically.
  • strategy · string · optionnel
    ``"balanced"`` only in Phase 2; future variants reserved.

  Exemple d'appel

  {"name": "cricket_build_dream11_team", "arguments": {"venue": "texte", "team_a": "texte", "team_b": "texte", "match_id": "texte", "strategy": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_captain_recommendation≈ 557 tokens

  Return the top-3 captain candidates ranked by projected points. IPL venues only (pitch seed is IPL grounds). Test/international matches and unknown venues fail rather than inventing a ranking. Same-role players often tie: projections use default form 55 and default opposition 0.5, not per-player history. Args: match_id: CricAPI match identifier; resolves team_a/team_b/venue automatically. team_a: First team code/name. Required if match_id is absent. team_b: Second team code/name. Required if match_id is absent. venue: Venue key/name (IPL ground, e.g. ``wankhede``). Required if match_id is absent. Returns: data.candidates: list of 3 dicts with name/role/team/projected_points. meta.source: model:captain_score. meta.estimated: true.

  Paramètres, retour & exemple (4)

  Paramètres

  • venue · ? · optionnel
    Venue key/name (IPL ground, e.g. ``wankhede``). Required if match_id is absent.
  • team_a · ? · optionnel
    First team code/name. Required if match_id is absent.
  • team_b · ? · optionnel
    Second team code/name. Required if match_id is absent.
  • match_id · ? · optionnel
    CricAPI match identifier; resolves team_a/team_b/venue automatically.

  Exemple d'appel

  {"name": "cricket_captain_recommendation", "arguments": {"venue": "texte", "team_a": "texte", "team_b": "texte", "match_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_differential_picks≈ 589 tokens

  Suggest low-ownership picks with positive projected upside. Ownership is *estimated* — proxied by credit weight (lower-credit players tend to have lower ownership), not real ownership data. Flagged ``estimated: true`` in the response. Args: match_id: CricAPI match identifier; resolves team_a/team_b/venue automatically. team_a: First team code/name. Required if match_id is absent. team_b: Second team code/name. Required if match_id is absent. venue: Venue key/name. Required if match_id is absent. ownership_threshold: percent ownership cap; affects estimated label. Returns: data.picks: list of {name, role, team, credits, projected_points, estimated_ownership_pct}. meta.source: model:captain_score (filtered). meta.estimated: true.

  Paramètres, retour & exemple (5)

  Paramètres

  • venue · ? · optionnel
    Venue key/name. Required if match_id is absent.
  • team_a · ? · optionnel
    First team code/name. Required if match_id is absent.
  • team_b · ? · optionnel
    Second team code/name. Required if match_id is absent.
  • match_id · ? · optionnel
    CricAPI match identifier; resolves team_a/team_b/venue automatically.
  • ownership_threshold · integer · optionnel
    percent ownership cap; affects estimated label.

  Exemple d'appel

  {"name": "cricket_differential_picks", "arguments": {"venue": "texte", "team_a": "texte", "team_b": "texte", "match_id": "texte", "ownership_threshold": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_find_value_bets≈ 562 tokens

  Compare model probabilities against market-implied IPL odds. Requires THEODDS_KEY. NOTE: cricket has no calibrated team-strength model wired yet (unlike the football Elo/Poisson path), so this tool currently returns an EMPTY ``value_bets`` list — scoring an edge against a neutral 50/50 prior would flag every market underdog, which would be misleading. It still reports how many events were screened so callers know odds were available. For raw de-vigged prices use ``cricket_get_live_odds``. Real edge detection lands when a cricket win model is wired (see cricket_head_to_head). Args: team: Optional team name to filter events (case-insensitive substring). Omit to scan every IPL odds event. min_edge: Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05. Currently informational only (no bets emitted). Returns: data.value_bets: always ``[]`` until a cricket model is wired. data.events_analysed: count of events screened (both teams present). data.model: ``"neutral_baseline"``. data.note: why no bets are emitted. meta.estimated: true.

  Paramètres, retour & exemple (2)

  Paramètres

  • team · ? · optionnel
    Optional team name to filter events (case-insensitive substring). Omit to scan every IPL odds event.
  • min_edge · number · optionnel
    Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05. Currently informational only (no bets emitted).

  Exemple d'appel

  {"name": "cricket_find_value_bets", "arguments": {"team": "texte", "min_edge": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_live_matches≈ 242 tokens

  Return all currently live cricket matches across all series. Returns: data.matches: list of live match objects (team names, score, status). meta.source: which adapter served the response. meta.is_stale: true if data is from stale cache.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "cricket_get_live_matches", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_live_odds≈ 525 tokens

  Return live market head-to-head odds for upcoming/live IPL matches. IPL only (~March-May). An empty ``events`` list outside that window is a successful empty market, not an outage. Not international/Test/other T20 leagues. For World Cup 2026 football odds use ``football_get_odds``. Sourced from The Odds API (requires THEODDS_KEY). Without a key the call returns a clean ALL_SOURCES_FAILED envelope rather than crashing. Args: team: Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to return every IPL event. The Odds API uses its own opaque event ids, so a CricAPI match_id cannot be resolved to an event yet — filtering is by team name. Returns: data.events: list of {event_id, home, away, commence_time, bookmakers: [{name, home, away}]} with decimal h2h prices per bookmaker. Empty when no IPL events are listed (typical off-season). meta.source: adapter that served the data (theodds / cache:stale).

  Paramètres, retour & exemple (1)

  Paramètres

  • team · ? · optionnel
    Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to return every IPL event. The Odds API uses its own opaque event ids, so a CricAPI match_id cannot be resolved to an event yet — filtering is by team name.

  Exemple d'appel

  {"name": "cricket_get_live_odds", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_pitch_report≈ 286 tokens

  Summarise pitch characteristics for a venue. Args: venue: Venue key (e.g. ``wankhede``), official name, or city. Returns: data: {batting_friendly 0..1, expected_first_inn, recommendation, venue, pitch_type}. meta.source: which adapter served the venue record.

  Paramètres, retour & exemple (1)

  Paramètres

  • venue · string · requis
    Venue key (e.g. ``wankhede``), official name, or city.

  Exemple d'appel

  {"name": "cricket_get_pitch_report", "arguments": {"venue": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_points_table≈ 284 tokens

  Return the points table / standings for a cricket series. Args: series_id: The series identifier (e.g. IPL 2026 series ID from CricAPI). Returns: data: points table rows with team, P, W, L, NRR, Points. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • series_id · string · requis
    The series identifier (e.g. IPL 2026 series ID from CricAPI).

  Exemple d'appel

  {"name": "cricket_get_points_table", "arguments": {"series_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_schedule≈ 431 tokens

  Return the upcoming match schedule, optionally filtered by series. Args: series_id: Optional. Filter to a specific series. If omitted, returns all upcoming fixtures across all active series. limit: Max matches to return, 1..200 (default 50). offset: Number of matches to skip for paging (default 0). Returns: data.matches: page of upcoming matches with teams, date, venue. data.pagination: {total, count, offset, limit, has_more, next_offset}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (3)

  Paramètres

  • limit · integer · optionnel
    Max matches to return, 1..200 (default 50).
  • offset · integer · optionnel
    Number of matches to skip for paging (default 0).
  • series_id · ? · optionnel
    Optional. Filter to a specific series. If omitted, returns all upcoming fixtures across all active series.

  Exemple d'appel

  {"name": "cricket_get_schedule", "arguments": {"limit": 1, "offset": 1, "series_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_scorecard≈ 280 tokens

  Return the full scorecard for a specific match. Args: match_id: The match identifier (e.g. from cricket_get_live_matches). Returns: data: full scorecard with innings, partnerships, bowling figures. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • match_id · string · requis
    The match identifier (e.g. from cricket_get_live_matches).

  Exemple d'appel

  {"name": "cricket_get_scorecard", "arguments": {"match_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_get_squad≈ 376 tokens

  Return the squad roster for a cricket team, optionally for a specific series. Args: team: Team code or name (e.g. "MI", "CSK", "IND", "AUS"). series_id: Optional. Series ID to pull the tournament-specific squad. If omitted, falls back to static seed data. Returns: data.players: list of players with name, role, and credits. meta.source: adapter that served the data (cricapi / static_seed).

  Paramètres, retour & exemple (2)

  Paramètres

  • team · string · requis
    Team code or name (e.g. "MI", "CSK", "IND", "AUS").
  • series_id · ? · optionnel
    Optional. Series ID to pull the tournament-specific squad. If omitted, falls back to static seed data.

  Exemple d'appel

  {"name": "cricket_get_squad", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_head_to_head≈ 352 tokens

  Compare two cricket teams head-to-head using squad form and player stats. Args: team_a: First team code or name (e.g. "MI", "India"). team_b: Second team code or name (e.g. "CSK", "Australia"). Returns: data: {team_a, team_b, team_a_edge_count, team_b_edge_count, key_players_a, key_players_b, h2h_win_rate_a, h2h_win_rate_b, win_prob_a, win_prob_b}. meta.estimated: true.

  Paramètres, retour & exemple (2)

  Paramètres

  • team_a · string · requis
    First team code or name (e.g. "MI", "India").
  • team_b · string · requis
    Second team code or name (e.g. "CSK", "Australia").

  Exemple d'appel

  {"name": "cricket_head_to_head", "arguments": {"team_a": "texte", "team_b": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_player_form_index≈ 315 tokens

  Report a 0-100 form score for a player using the player_stats chain. Args: player_id: Upstream player identifier (CricAPI/Cricbuzz id). Returns: data.form_score: 0..100 indicator. data.trend: "rising" / "stable" / "falling". data.samples: how many recent innings were available. meta.source: which adapter served the underlying stats. meta.estimated: true.

  Paramètres, retour & exemple (1)

  Paramètres

  • player_id · string · requis
    Upstream player identifier (CricAPI/Cricbuzz id).

  Exemple d'appel

  {"name": "cricket_player_form_index", "arguments": {"player_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cricket_player_matchup≈ 335 tokens

  Analyse the head-to-head matchup between two cricket players based on role and career stats. Args: player_a: Player ID or name for the first player. player_b: Player ID or name for the second player. Returns: data: {matchup_type, edge_holder, edge_reason, signals, role_a, role_b}. meta.estimated: true — heuristic model, not ball-by-ball H2H data.

  Paramètres, retour & exemple (2)

  Paramètres

  • player_a · string · requis
    Player ID or name for the first player.
  • player_b · string · requis
    Player ID or name for the second player.

  Exemple d'appel

  {"name": "cricket_player_matchup", "arguments": {"player_a": "texte", "player_b": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• cross_sport_build_accumulator≈ 321 tokens

  Model the joint probability of multiple outcomes across football and cricket. Args: legs: Total legs across both sports (2-8). Default 3. min_edge: Minimum edge per leg. Default 0.05. Returns: data: same shape as football_build_accumulator, with sport field per leg. meta.estimated: true.

  Paramètres, retour & exemple (2)

  Paramètres

  • legs · integer · optionnel
    Total legs across both sports (2-8). Default 3.
  • min_edge · number · optionnel
    Minimum edge per leg. Default 0.05.

  Exemple d'appel

  {"name": "cross_sport_build_accumulator", "arguments": {"legs": 1, "min_edge": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_drivers≈ 266 tokens

  Return driver list for a specific F1 session. Args: session_key: OpenF1 session identifier. Returns: data.drivers: list of driver objects with driver_number, full_name, team. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • session_key · integer · requis
    OpenF1 session identifier.

  Exemple d'appel

  {"name": "f1_get_drivers", "arguments": {"session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_lap_times≈ 465 tokens

  Return lap times for a driver in a specific F1 session. Args: session_key: OpenF1 session identifier. driver_number: Driver's race number (e.g. 1 for Verstappen). limit: Max laps to return, 1..200 (default 100 — covers most full races). offset: Number of laps to skip for paging (default 0). Returns: data.laps: page of lap objects with lap_number and lap_duration. OpenF1 does not put compound/tyre_life here — those live on the stints endpoint. data.pagination: {total, count, offset, limit, has_more, next_offset}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (4)

  Paramètres

  • limit · integer · optionnel
    Max laps to return, 1..200 (default 100 — covers most full races).
  • offset · integer · optionnel
    Number of laps to skip for paging (default 0).
  • session_key · integer · requis
    OpenF1 session identifier.
  • driver_number · integer · requis
    Driver's race number (e.g. 1 for Verstappen).

  Exemple d'appel

  {"name": "f1_get_lap_times", "arguments": {"session_key": 1, "driver_number": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_race_results≈ 340 tokens

  Return the final classification for one F1 race, keyed by year and round. Args: year: Championship year (e.g. 2025). round: Round number within the season (1-based; e.g. 1 for the opener). Returns: data.results: Ergast/Jolpica RaceTable payload — finishing order, times, grid positions, points, and fastest laps for the race. meta.source: adapter that served the data.

  Paramètres, retour & exemple (2)

  Paramètres

  • year · integer · requis
    Championship year (e.g. 2025).
  • round · integer · requis
    Round number within the season (1-based; e.g. 1 for the opener).

  Exemple d'appel

  {"name": "f1_get_race_results", "arguments": {"year": 1, "round": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_sessions≈ 326 tokens

  Return F1 sessions for a given year, optionally filtered by country. Args: year: Championship year (e.g. 2025). country: Optional country name to filter (e.g. "Monaco"). Returns: data.sessions: list of session objects with session_key, session_type, date. meta.source: adapter that served the data.

  Paramètres, retour & exemple (2)

  Paramètres

  • year · integer · requis
    Championship year (e.g. 2025).
  • country · ? · optionnel
    Optional country name to filter (e.g. "Monaco").

  Exemple d'appel

  {"name": "f1_get_sessions", "arguments": {"year": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_standings≈ 335 tokens

  Return F1 driver and constructor championship standings for a year. Use this for "who is leading / who will win the F1 championship this year". There is no F1 title Monte Carlo — current points and position are the answer. This is not a cricket or football tool. Args: year: Championship year (e.g. 2026). Returns: data.driver_standings: driver championship positions and points. data.constructor_standings: constructor championship positions and points. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • year · integer · requis
    Championship year (e.g. 2026).

  Exemple d'appel

  {"name": "f1_get_standings", "arguments": {"year": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_get_weather≈ 266 tokens

  Return weather data for a specific F1 session. Args: session_key: OpenF1 session identifier. Returns: data.weather: list of weather snapshots with temperature, rainfall, wind. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • session_key · integer · requis
    OpenF1 session identifier.

  Exemple d'appel

  {"name": "f1_get_weather", "arguments": {"session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_head_to_head_pace≈ 344 tokens

  Compare lap-time pace distribution between two drivers in a session. Args: session_key: OpenF1 session identifier. driver_a: First driver's race number. driver_b: Second driver's race number. Returns: data: {driver_a_avg_s, driver_b_avg_s, delta_s, faster_driver}. meta.estimated: true.

  Paramètres, retour & exemple (3)

  Paramètres

  • driver_a · integer · requis
    First driver's race number.
  • driver_b · integer · requis
    Second driver's race number.
  • session_key · integer · requis
    OpenF1 session identifier.

  Exemple d'appel

  {"name": "f1_head_to_head_pace", "arguments": {"driver_a": 1, "driver_b": 1, "session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_predict_pit_strategy≈ 636 tokens

  Predict the optimal pit-stop strategy for a driver in an F1 race session. Args: session_key: OpenF1 session identifier for a recorded race. driver_number: Driver's race number (e.g. 1 for Verstappen). current_lap: Current lap to project from (default 1 = full race ahead). total_laps: Total race laps. If omitted, inferred from the highest observed lap_number in the fetched laps (correct for Monaco 78 / Spa 44), falling back to 57 when no laps are available. An explicit value always wins. Returns: data.stop_laps: recommended pit laps. data.compound_sequence: tyre compounds for each stint. data.expected_finish_position: currently always None (not modelled). data.confidence: 0.0-1.0 model confidence. meta.total_laps: race length used (explicit arg, else inferred from laps). meta.estimated: true. Example: f1_predict_pit_strategy(session_key=9158, driver_number=1) f1_predict_pit_strategy(session_key=9158, driver_number=16, current_lap=20, total_laps=78)

  Paramètres, retour & exemple (4)

  Paramètres

  • total_laps · ? · optionnel
    Total race laps. If omitted, inferred from the highest observed lap_number in the fetched laps (correct for Monaco 78 / Spa 44), falling back to 57 when no laps are available. An explicit value always wins.
  • current_lap · integer · optionnel
    Current lap to project from (default 1 = full race ahead).
  • session_key · integer · requis
    OpenF1 session identifier for a recorded race.
  • driver_number · integer · requis
    Driver's race number (e.g. 1 for Verstappen).

  Exemple d'appel

  {"name": "f1_predict_pit_strategy", "arguments": {"session_key": 1, "driver_number": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_qualifying_analysis≈ 328 tokens

  Analyse a qualifying session: best lap per driver, gap to pole, projected grid. Args: session_key: OpenF1 session identifier for a Qualifying session. Returns: data.grid: [{position, driver_number, full_name, team_name, best_lap_gap_s}]. data.pole_time_s: pole lap duration in seconds. data.drivers_analysed: count of drivers with valid laps. meta.estimated: true — grid derived from session laps, not official timing.

  Paramètres, retour & exemple (1)

  Paramètres

  • session_key · integer · requis
    OpenF1 session identifier for a Qualifying session.

  Exemple d'appel

  {"name": "f1_qualifying_analysis", "arguments": {"session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_race_pace_compare≈ 356 tokens

  Compare race-pace and tyre degradation between two F1 drivers in a session. Args: session_key: OpenF1 session identifier. driver_a: First driver's race number. driver_b: Second driver's race number. Returns: data: {by_compound, overall_faster, compounds_compared}. meta.estimated: true — degradation model fit, not official timing.

  Paramètres, retour & exemple (3)

  Paramètres

  • driver_a · integer · requis
    First driver's race number.
  • driver_b · integer · requis
    Second driver's race number.
  • session_key · integer · requis
    OpenF1 session identifier.

  Exemple d'appel

  {"name": "f1_race_pace_compare", "arguments": {"driver_a": 1, "driver_b": 1, "session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_tyre_degradation≈ 362 tokens

  Fit a tyre degradation model for a driver + compound in a session. Args: session_key: OpenF1 session identifier. driver_number: Driver's race number. compound: Tyre compound (SOFT, MEDIUM, HARD, INTER, WET). Returns: data: {intercept, slope, residual_std, sample_count}. meta.estimated: true — model output, not telemetry oracle.

  Paramètres, retour & exemple (3)

  Paramètres

  • compound · string · requis
    Tyre compound (SOFT, MEDIUM, HARD, INTER, WET).
  • session_key · integer · requis
    OpenF1 session identifier.
  • driver_number · integer · requis
    Driver's race number.

  Exemple d'appel

  {"name": "f1_tyre_degradation", "arguments": {"compound": "texte", "session_key": 1, "driver_number": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_undercut_window≈ 397 tokens

  Estimate whether an undercut is viable for the attacker against the target. Args: session_key: OpenF1 session identifier. attacker_number: Attacking driver's race number. target_number: Target driver's race number. current_lap: Current lap number in the race. Returns: data: {laps_to_clear, viable, marginal}. meta.estimated: true.

  Paramètres, retour & exemple (4)

  Paramètres

  • current_lap · integer · requis
    Current lap number in the race.
  • session_key · integer · requis
    OpenF1 session identifier.
  • target_number · integer · requis
    Target driver's race number.
  • attacker_number · integer · requis
    Attacking driver's race number.

  Exemple d'appel

  {"name": "f1_undercut_window", "arguments": {"current_lap": 1, "session_key": 1, "target_number": 1, "attacker_number": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• f1_weather_strategy_impact≈ 273 tokens

  Analyse weather data and recommend compound or pit-window adjustments. Args: session_key: OpenF1 session identifier. Returns: data: {has_rain, avg_track_temp_c, compound_recommendation, recommendation}. meta.estimated: true.

  Paramètres, retour & exemple (1)

  Paramètres

  • session_key · integer · requis
    OpenF1 session identifier.

  Exemple d'appel

  {"name": "f1_weather_strategy_impact", "arguments": {"session_key": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_build_accumulator≈ 370 tokens

  Model the joint probability of several match outcomes from the top model-vs-market gaps. Calls ``football_find_value_bets`` internally to fetch live odds, then selects the strongest legs and combines them under the joint-probability model. Args: legs: Number of legs (2-8). Default 3. min_edge: Minimum edge threshold per leg. Default 0.05. Returns: data: {legs, legs_used, combined_odds, combined_model_prob, combined_edge, risk_flag, independence_warning}. meta.estimated: true.

  Paramètres, retour & exemple (2)

  Paramètres

  • legs · integer · optionnel
    Number of legs (2-8). Default 3.
  • min_edge · number · optionnel
    Minimum edge threshold per leg. Default 0.05.

  Exemple d'appel

  {"name": "football_build_accumulator", "arguments": {"legs": 1, "min_edge": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_find_value_bets≈ 547 tokens

  Surface the largest gaps between the model's win probability and the market. De-vigs each market's 1X2 decimal odds (removes the margin so implied probabilities sum to 1) and compares them to this server's own match-outcome probabilities — the same Elo/Poisson path ``football_match_predictor`` uses. Where the model probability exceeds the de-vigged market probability by at least ``min_edge``, the outcome is flagged with its edge and the model's fair odds. Args: team: Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to scan every WC 2026 odds event. min_edge: Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05 (5 percentage points). Returns: data.value_bets: list of {event_id, home, away, outcome, model_prob, fair_odds, market_odds, edge, bookmaker}, sorted by edge descending. data.events_analysed: events with both teams rated (model-comparable). meta.estimated: true. meta.is_stale reflects the odds freshness.

  Paramètres, retour & exemple (2)

  Paramètres

  • team · ? · optionnel
    Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to scan every WC 2026 odds event.
  • min_edge · number · optionnel
    Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05 (5 percentage points).

  Exemple d'appel

  {"name": "football_find_value_bets", "arguments": {"team": "texte", "min_edge": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_form_trends≈ 295 tokens

  Return rolling form, goal record, and xG trend for a football team. Args: team: Team name (e.g. "Brazil", "Argentina"). Returns: data: {form_string, wins, draws, losses, goals_scored, goals_conceded, xg_for, xg_against, recent_trend, matches_analysed}. meta.estimated: true — derived from available fixture data.

  Paramètres, retour & exemple (1)

  Paramètres

  • team · string · requis
    Team name (e.g. "Brazil", "Argentina").

  Exemple d'appel

  {"name": "football_form_trends", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_fixtures≈ 356 tokens

  Return World Cup 2026 fixtures (live providers, else the group schedule). Args: limit: Max fixtures to return, 1..200 (default 50). offset: Number of fixtures to skip for paging (default 0). Returns: data.fixtures: page of {home, away, date/group, status, home_goals, away_goals}. data.pagination: {total, count, offset, limit, has_more, next_offset}. meta.source: adapter that served the data (static_seed = group schedule only).

  Paramètres, retour & exemple (2)

  Paramètres

  • limit · integer · optionnel
    Max fixtures to return, 1..200 (default 50).
  • offset · integer · optionnel
    Number of fixtures to skip for paging (default 0).

  Exemple d'appel

  {"name": "football_get_fixtures", "arguments": {"limit": 1, "offset": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_groups≈ 255 tokens

  Return the FIFA World Cup 2026 group draw and advancement format. Returns: data.groups: {group_letter: [4 team codes]} for all 12 groups. data.format: 48-team / 12-group / top-2 + 8-best-thirds rule. data.teams: team-code -> {name, fifa_code} metadata. meta.source: adapter that served the data.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "football_get_groups", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_match_stats≈ 327 tokens

  Return a team's aggregate World Cup tournament statistics. Network-only enrichment: requires a configured API-Football (or football-data.org) key. There is no offline static fallback, so without a key the call returns a clean ALL_SOURCES_FAILED envelope. Args: team: API-Football numeric team id (not a country code). Returns: data.team_stats: {team, played, wins, goals_for, goals_against}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • team · integer · requis
    API-Football numeric team id (not a country code).

  Exemple d'appel

  {"name": "football_get_match_stats", "arguments": {"team": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_odds≈ 384 tokens

  Return live market head-to-head odds for upcoming World Cup 2026 matches. Sourced from The Odds API (requires THEODDS_KEY). Without a key the call returns a clean ALL_SOURCES_FAILED envelope rather than crashing. Args: team: Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to return every WC event. Returns: data.events: list of {event_id, home, away, commence_time, bookmakers: [{name, home, draw, away}]} with decimal 1X2 prices per bookmaker. meta.source: adapter that served the data (theodds / cache:stale).

  Paramètres, retour & exemple (1)

  Paramètres

  • team · ? · optionnel
    Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to return every WC event.

  Exemple d'appel

  {"name": "football_get_odds", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_squad≈ 311 tokens

  Return a national team's World Cup squad. Args: team: Team code or name (e.g. "ARG"). Without an API-Football key, the static seed serves an empty-but-valid squad (rosters are a follow-up). Returns: data.squad: list of {name, number, position, age}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (1)

  Paramètres

  • team · string · requis
    Team code or name (e.g. "ARG"). Without an API-Football key, the static seed serves an empty-but-valid squad (rosters are a follow-up).

  Exemple d'appel

  {"name": "football_get_squad", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_standings≈ 339 tokens

  Return current World Cup 2026 group standings. Args: limit: Max standing rows to return, 1..200 (default 50). offset: Number of rows to skip for paging (default 0). Returns: data.standings: page of {rank, team, group, points, played, goals_diff}. data.pagination: {total, count, offset, limit, has_more, next_offset}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (2)

  Paramètres

  • limit · integer · optionnel
    Max standing rows to return, 1..200 (default 50).
  • offset · integer · optionnel
    Number of rows to skip for paging (default 0).

  Exemple d'appel

  {"name": "football_get_standings", "arguments": {"limit": 1, "offset": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_get_top_scorers≈ 217 tokens

  Return the World Cup 2026 top scorers. Returns: data.scorers: list of {name, team, goals, assists}. meta.source: adapter that served the data.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "football_get_top_scorers", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_knockout_path≈ 359 tokens

  Round-by-round survival probabilities for one team in the full sim. Args: team: Team code (e.g. "FRA"). iterations: Number of tournament simulations (clamped to 100..20000). seed: Optional RNG seed. Returns: data: {team, reach_r32, reach_r16, reach_qf, reach_sf, reach_final, win}. meta.estimated: true.

  Paramètres, retour & exemple (3)

  Paramètres

  • seed · ? · optionnel
    Optional RNG seed.
  • team · string · requis
    Team code (e.g. "FRA").
  • iterations · integer · optionnel
    Number of tournament simulations (clamped to 100..20000).

  Exemple d'appel

  {"name": "football_knockout_path", "arguments": {"team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_match_predictor≈ 346 tokens

  Predict a single match: most likely scoreline + outcome probabilities. Args: home_team: First team code. away_team: Second team code. neutral: True for a neutral venue (World Cup default). Returns: data: {most_likely_score, home_win, draw, away_win, predicted_winner}. meta.estimated: true.

  Paramètres, retour & exemple (3)

  Paramètres

  • neutral · boolean · optionnel
    True for a neutral venue (World Cup default).
  • away_team · string · requis
    Second team code.
  • home_team · string · requis
    First team code.

  Exemple d'appel

  {"name": "football_match_predictor", "arguments": {"away_team": "texte", "home_team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_simulate_bracket≈ 486 tokens

  Monte Carlo the full World Cup 2026 — per-team round + title probabilities. Simulates all 12 groups, advances the top 2 + 8 best third-placed teams to a 32-team knockout, and plays it to a champion, ``iterations`` times. Args: iterations: Number of tournament simulations (clamped to 100..20000; ~10000 gives stable ±2% probabilities). seed: Optional RNG seed for reproducible output. Returns: data.teams: {code: {reach_r32, reach_r16, reach_qf, reach_sf, reach_final, win}} sorted by win probability descending. data.champion: most likely winner. data.iterations: iterations run. meta.estimated: true. meta.conditioned_matches: completed matches locked in (played group results fixed, decided knockout ties locked). Example: football_simulate_bracket() football_simulate_bracket(iterations=20000, seed=42)

  Paramètres, retour & exemple (2)

  Paramètres

  • seed · ? · optionnel
    Optional RNG seed for reproducible output.
  • iterations · integer · optionnel
    Number of tournament simulations (clamped to 100..20000; ~10000 gives stable ±2% probabilities).

  Exemple d'appel

  {"name": "football_simulate_bracket", "arguments": {"seed": "texte", "iterations": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_simulate_group≈ 352 tokens

  Monte Carlo one group within the full 12-group qualification context. Args: group: Group letter A-L. iterations: Number of simulations (clamped to 100..20000). Returns: data.teams: Per-team position probabilities, p_auto_advance, p_best_third_advance, truthful combined p_advance, and avg_points. data.iterations: iterations actually run. meta.estimated: true. meta.conditioned_matches: completed matches locked in.

  Paramètres, retour & exemple (2)

  Paramètres

  • group · string · requis
    Group letter A-L.
  • iterations · integer · optionnel
    Number of simulations (clamped to 100..20000).

  Exemple d'appel

  {"name": "football_simulate_group", "arguments": {"group": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• football_xg_model≈ 368 tokens

  Estimate a match's expected goals and win/draw/loss probabilities. Args: home_team: First team code (e.g. "ARG"). away_team: Second team code (e.g. "BRA"). neutral: True for a neutral venue (no home advantage). World Cup default. Returns: data: {expected_home_goals, expected_away_goals, home_win, draw, away_win}. meta.estimated: true.

  Paramètres, retour & exemple (3)

  Paramètres

  • neutral · boolean · optionnel
    True for a neutral venue (no home advantage). World Cup default.
  • away_team · string · requis
    Second team code (e.g. "BRA").
  • home_team · string · requis
    First team code (e.g. "ARG").

  Exemple d'appel

  {"name": "football_xg_model", "arguments": {"away_team": "texte", "home_team": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

• sportiq_health≈ 222 tokens

  Report cache backend, per-adapter healthcheck, and quota status. Returns: HealthReport-shaped dict with `cache_backend`, `cache_ok`, `adapters` (per-source ok/detail), and `quotas`.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "sportiq_health", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"data": "texte", "meta": "texte", "error": "texte"}}

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Source

https://sportiq.utkarshgupta.org/mcp