Connect io.github.Ninjabeam20/sportiq-mcp and your agent gets 44 tools, among them cricket_build_dream11_team, cricket_captain_recommendation, cricket_differential_picks. It answers at https://sportiq.utkarshgupta.org/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 3 of 6 times since 11 September 2026; the last check, on 20 October 2026, succeeded.
MCP tools for FIFA World Cup 2026 football, Formula 1, and IPL cricket — sims, strategy, fantasy.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
cricket_build_dream11_team | 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 Inputs: match_id, team_a, team_b, venue, strategy |
cricket_captain_recommendation | 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 de Inputs: match_id, team_a, team_b, venue |
cricket_differential_picks | 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: Inputs: match_id, team_a, team_b, venue, ownership_threshold |
cricket_find_value_bets | 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`` Inputs: team, min_edge |
cricket_get_live_matches | 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. |
cricket_get_live_odds | 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 202 Inputs: team |
cricket_get_pitch_report | 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 serve Inputs: venue |
cricket_get_points_table | 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 Inputs: series_id |
cricket_get_schedule | 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) Inputs: series_id, limit, offset |
cricket_get_scorecard | 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. Inputs: match_id |
cricket_get_squad | 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 st Inputs: team, series_id |
cricket_head_to_head | 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_co Inputs: team_a, team_b |
cricket_player_form_index | 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: h Inputs: player_id |
cricket_player_matchup | 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_holde Inputs: player_a, player_b |
cross_sport_build_accumulator | 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, Inputs: legs, min_edge |
f1_get_drivers | 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. Inputs: session_key |
f1_get_lap_times | 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). off Inputs: session_key, driver_number, limit, offset |
f1_get_race_results | 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 pay Inputs: year, round |
f1_get_sessions | 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, sess Inputs: year, country |
f1_get_standings | 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 cri Inputs: year |
f1_get_weather | 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. Inputs: session_key |
f1_head_to_head_pace | 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, Inputs: session_key, driver_a, driver_b |
f1_predict_pit_strategy | 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 fro Inputs: session_key, driver_number, current_lap, total_laps |
f1_qualifying_analysis | 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}]. da Inputs: session_key |
f1_race_pace_compare | 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_fast Inputs: session_key, driver_a, driver_b |
f1_tyre_degradation | 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 Inputs: session_key, driver_number, compound |
f1_undercut_window | 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 Inputs: session_key, attacker_number, target_number, current_lap |
f1_weather_strategy_impact | 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. Inputs: session_key |
football_build_accumulator | 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. Inputs: legs, min_edge |
football_find_value_bets | 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 — Inputs: team, min_edge |
football_form_trends | 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, matche Inputs: team |
football_get_fixtures | 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 Inputs: limit, offset |
football_get_groups | 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_cod |
football_get_match_stats | 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_FA Inputs: team |
football_get_odds | 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 n Inputs: team |
football_get_squad | 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, positi Inputs: team |
football_get_standings | 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_ Inputs: limit, offset |
football_get_top_scorers | Return the World Cup 2026 top scorers. Returns: data.scorers: list of {name, team, goals, assists}. meta.source: adapter that served the data. |
football_knockout_path | 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_r1 Inputs: team, iterations, seed |
football_match_predictor | 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, Inputs: home_team, away_team, neutral |
football_simulate_bracket, football_simulate_group, football_xg_model, sportiq_health
Every block below points at https://sportiq.utkarshgupta.org/mcp. Pick your client and copy.
claude mcp add --transport http io-github-ninjabeam20-sportiq-mc https://sportiq.utkarshgupta.org/mcp
{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://sportiq.utkarshgupta.org/mcp"]
}
}
}{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"servers": {
"io-github-ninjabeam20-sportiq-mc": {
"type": "http",
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"context_servers": {
"io-github-ninjabeam20-sportiq-mc": {
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"serverUrl": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}name: io.github.Ninjabeam20/sportiq-mcp
version: 0.0.1
schema: v1
mcpServers:
- name: io.github.Ninjabeam20/sportiq-mcp
type: streamable-http
url: https://sportiq.utkarshgupta.org/mcp{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"httpUrl": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"type": "http",
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}{
"mcpServers": {
"io-github-ninjabeam20-sportiq-mc": {
"url": "https://sportiq.utkarshgupta.org/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fsportiq.utkarshgupta.org%2Fmcp&type=streamable_http&id=io-github-ninjabeam20-sportiq-mc&name=io.github.Ninjabeam20/sportiq-mcp
It answered our last check on 20 October 2026 in 514 ms. Over 6 checks since 11 September 2026 it answered 3. Status here comes from Neuronto's own probes, not from the publisher.
44, as returned by the server's own tools/list on 26 September 2026: cricket_build_dream11_team, cricket_captain_recommendation, cricket_differential_picks, cricket_find_value_bets, cricket_get_live_matches, cricket_get_live_odds, cricket_get_pitch_report, cricket_get_points_table, and 36 more.
It answered our last check on 20 October 2026 in 514 ms. Over 6 checks since 11 September 2026 it answered 3.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://sportiq.utkarshgupta.org/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.ninjabeam20. Endpoint host: sportiq.utkarshgupta.org. ARD identifier: urn:air:io.github.ninjabeam20:mcp:sportiq-mcp.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.