Skip to main content
Glama
390,808 tools. Last updated 2026-08-04 15:35

"league of legends" matching MCP tools:

  • Summary of live flight activity over a named region — total aircraft count, by-country breakdown of operators, average altitude, ground vs in-air split. Built for "is airspace open / closed" style geopolitical bets (Polymarket "Iran closes its airspace by X", "Strait of Hormuz traffic returns to normal", "Russia closes airspace"). Supported regions: Iran, Israel, Syria, Ukraine, Russia, Taiwan, North Korea, South China Sea, Yemen, Strait of Hormuz, Taiwan Strait, Red Sea, Saudi Arabia, Gulf of Aden, Lebanon.
    Connector
  • Search the Analytics Legends market-news corpus. It is watched FOR SAP analytics (Datasphere, Business Data Cloud, SAC, BW/4HANA, Databricks, the 2027/2030 maintenance window), but it is NOT an all-SAP corpus: measured 2026-07-30, ~84 % of active rows sit in the `AI` category and are general enterprise-AI trade press (cloud platforms, model releases, funding rounds) with no SAP content at all. An UNFILTERED call therefore returns mostly non-SAP items — pass `query` or `category` when the question is about SAP, and never present an unfiltered page as 'the SAP analytics news'. Say what you actually got. Each item returns the Analytics Legends citation URL AND the upstream publisher's source_url — cite both, and prefer source_url when you need a page that certainly carries the item.
    Connector
  • Use this alone for user-specific connection, league, or account-status questions, and use it as the first data tool when a request needs the user's connected fantasy league data. Do not call for Flaim capability, permission, or generic setup how-to questions, and do not call for generic coding, scraping, weather, travel, betting, sports news, or other requests that do not need connected league data. For a normal selected-league request, call this once before any other data tool. For an explicit refresh request, call refresh_leagues first and then call this tool after success; call it again even if it ran earlier in the chat. Returns the user's full league landscape: allLeagues (all active leagues), defaultLeagues (per-sport defaults), and defaultLeague (populated only when a single league exists or defaultSport matches). For vague singular prompts, use defaultLeague when present; otherwise use the relevant sport entry in defaultLeagues. For explicit plural or comparative prompts (each, all, compare, across leagues/platforms), enumerate every matching league in allLeagues and call the target tool once per league. For a selected active league, call get_league_info next before the requested league-specific data tool. Skip get_league_info only when answering from session data alone or branching to get_ancient_history. season_year always represents the start year of the season. Read-only.
    Connector
  • Get players available to acquire in the specified fantasy league, optionally filtered by position. This is fantasy-league availability, not professional-contract status. ESPN percentOwned/percentStarted are the percentages of all ESPN leagues where the player is rostered/started, not the share of rostered teams that start him. Yahoo percentOwned, when present, is Yahoo-wide; none is ownership within the selected league, and Sleeper provides no percentage. Label every reported percentage as an ESPN-wide roster/start rate or Yahoo-wide market rate. If a rate is missing, write "[Provider] market ownership rate: not provided"; do not repeat response field names or null values, call get_players, or offer a lookup. team/proTeam is the real-life club (FA means the provider lists no current pro team). Only ESPN status/waiverProcessDate represents fantasy acquisition state here. Call Yahoo/Sleeper rows "available players," never specifically free agents or waivers, and do not promise an immediate add. A returned player is already confirmed available in that league. For a returned list or field explanation, end after the requested facts—never add an "if you want" offer, qualitative ranking, recommendation, role, health, trend, or outlook. Translate ESPN status codes silently into plain language; never print raw codes such as FREEAGENT or WAIVERS. Use current web evidence before adding analysis or pickup recommendations. Follow get_user_session then get_league_info for the selected league; fan out once per league for comparisons. Use get_roster for a separate player-ownership question. Requires authentication on ESPN/Yahoo; Sleeper uses the public API. Read-only. Current date is 2026-08-04.
    Connector
  • Return a filtered slice of the resolved-pick ledger by tier, league, and result. Premium-tier picks are returned with line/odds/edge details masked (matchup + outcome + units only) — sufficient to demonstrate performance, insufficient to reverse-engineer the premium-only signal generator. Args: league: Optional league filter. tier: ``free`` for fully-public picks, ``premium`` for masked subscriber picks. result: WIN, LOSS, or PUSH. limit: Maximum rows (capped at 200). cursor: Zero-based result offset. Prefer get_track_record for new clients. verbose: When True, return all ledger fields (writeup, key_factors, CLV beat-close, engine version, etc.). Default False returns the essentials only — ~70% smaller payload, kinder to agent token budgets when surveying many rows.
    Connector
  • Scan today's whole slate in ONE call — each fixture with honest status + value/arb signal. The batch alternative to looping find_match → get_sharp_line per match. Returns every fixture in the filter with its status (finished is excluded from "live"), live score/clock, and a pre-computed value/arb signal; value/arb matches are sorted to the top and the list is truncated to ``limit`` (so truncation drops the quiet ones). Line movement is NOT included (that needs the opening lookup) — drill into a single fixture with get_opening_line. DETECTION ONLY / read-only. Args: sport: optional filter — "football" or "basketball". status: optional filter — "live" | "scheduled" | "finished". league: optional league filter — a name (fuzzy-matched, e.g. "World Cup") or an external id (lg_…). markets: optional — limit the value/arb scan to "1x2"/"asian_handicap"/"totals" (default all). period: optional — "full_time" or "half_time" (default both). min_edge_pct: value threshold for the per-match signal (default 1.0). min_margin_pct: arbitrage threshold for the per-match signal (default 0.0). only_signal: if true, return only fixtures that have a value or arb signal. format: odds format — decimal | hk | malay | american | indonesian | probability. limit: max entries to return, signal-first (default 20, max 100).
    Connector

Matching MCP Servers

Matching MCP Connectors

  • Read one Analytics Legends study BODY — the paid text behind list_studies' metadata. Requires a subscriber API key, Consultant tier or above. Bodies run to 38k words and exceed the 256 KiB response ceiling, so this tool serves STRUCTURE first: called without `section` it returns the section list and the introduction; pass `section` (a heading from that list, matched case-insensitively) to read one section. Find slugs and languages with list_studies.
    Connector
  • Get recent league transactions including adds, drops, waivers, and trades. Best used after get_user_session and usually after get_league_info so the model already knows the league's team names and owner/team mapping before summarizing activity. Each normalized transaction includes a date field (YYYY-MM-DD), type, status, week, and optional team_ids. When presenting results, organize by time period (today, yesterday, this week, older) AND by team within each period so the user can see both when moves happened and what each team did. Week handling is platform-specific: ESPN/Sleeper use week windows (default current + previous week), while Yahoo uses a recent 14-day timestamp window and ignores explicit week. Type support is also platform-specific: Sleeper supports add/drop/trade/waiver; Yahoo supports add/drop/trade plus pending waiver/pending_trade views for the authenticated user's own items; ESPN also supports failed_bid and trade lifecycle types (trade_proposal, trade_decline, trade_veto, trade_uphold). ESPN uses mTransactions2 for structured transaction data, and accepted trade player details are supplemented from the activity feed. ESPN responses include a "teams" map (team ID → display name) to resolve the numeric team_ids on each transaction, while Yahoo and Sleeper generally rely on get_league_info for team-name resolution. Use values from get_user_session. Read-only. Current date is 2026-08-04.
    Connector
  • Return today's free sports betting projections published by Olympus Bets Analytics. Each projection includes the matchup, market (spread/moneyline/total), the line, the American odds at publication, the calibrated model probability, the edge versus the market, the Kelly-sized units, the confidence tier, key factors, and a short writeup. These are PUBLIC projections — the same set published on https://app.olympus-bets.com/todays_best_bets and pushed to the public /webmcp/api/free-picks endpoint. Premium tier projections are not exposed here. Args: league: Optional league filter (e.g. "NBA", "NHL", "MLB", "CBB", "NFL", "SOCCER", "LOL", "GOLF"). Omit to return all leagues. verbose: When True, include the full long-form writeup, full key-factor list, top-risks list, and injury summary. Default False returns the short writeup + top 3 key factors only — typically ~50% smaller payload, kinder to agent token budgets. Set verbose=True when an agent specifically wants the detail (e.g., user asked "explain this pick"). Returns: ``{date, total, leagues_active, projections: [...]}``
    Connector
  • Return Olympus Bets Analytics' own self-graded model-quality metrics — NOT pick win rate. This is a different question than "did our picks win money?" (see get_performance_summary / get_track_record for that). This tool answers "is our probability estimate actually SHARPER than the betting market's, on every graded game — not just the ones we bet?" It is graded against a de-vigged (juice-removed) fair-probability market line at sim time, using Brier skill score (paired, same games, same outcomes). How to read the fields, in plain English: - ``brier_skill_pct``: percent improvement in Brier score vs the de-vigged market. POSITIVE = our model is sharper than the market. NEGATIVE = the market is sharper than us. Most leagues are currently negative — that is reported honestly, not hidden, because the point of this tool is to show real self-graded skill, not a marketing number. - ``model_weight_star`` (w*): the blend weight (0.0-1.0) our model earned in a model+market blend that minimizes log-loss. 0.0 means "defer entirely to the market's number"; 1.0 means "our number alone is already optimal." This is fit empirically per league/window, not asserted. - ``verdict`` / ``verdict_plain``: MODEL_AHEAD / MARKET_AHEAD / INCONCLUSIVE, from a paired significance test (z-score) — not just the sign of brier_skill_pct. - ``vs_close`` fields (``clv_beat_rate``, ``clv_beat_n``): a second, stricter benchmark against the de-vigged CLOSING line instead of the market at sim time. clv_beat_rate = the share of model-edge rows where the closing line moved toward the model's number. Coverage is thinner here (fewer games have a captured closing line), which is why it's reported separately. - ``n`` / ``reliable``: sample size behind each cell. Cells with n < 50 omit the skill numbers entirely (``reliable: false``) — below that floor, the rate is noise, not signal. Windows: ``30d`` (most current, smallest sample) and ``90d`` (steadier, larger sample). Use 90d as the primary read; use 30d to see if something is actively shifting. Freshness: the underlying file rebuilds daily (~12:50 UTC). If it is stale (>36h old), this tool returns ``{"status": "updating", ...}`` instead of presenting old numbers as current — never treat a missing ``windows`` key as "no skill data," check ``status`` first. Args: league: Optional league filter (e.g. "MLB", "NHL"). Omit for all leagues covered by the scoreboard (NBA, NHL, MLB, SOCCER, WNBA, TENNIS, LOL, CS2, GOLF, WC — CFB/NFL/CBB not yet in-season/covered). Returns: ``{status, generated_at, benchmark, close_benchmark, sample_floor_n, windows: {"30d": {...}, "90d": {...}}}`` where each window has ``overall`` (blended-across-leagues cell) and ``by_league`` (list of per-league cells, each carrying its own ``league`` code).
    Connector
  • List today's (UTC) fixtures — "what games are on today / right now?". Each fixture carries its status, live score, the live match ``clock`` (upstream minute text, verbatim e.g. "1h 25" / "2h 47" / "ht") when in-running, and a ready-to-read ``summary`` (live score & clock, or the kickoff time). Read ``clock`` for the real minute rather than estimating it from kickoff. ``clock`` is null pre-match. Args: sport: optional filter — "football" or "basketball". status: optional filter — "live", "scheduled" or "finished". league: optional league filter — a name (fuzzy-matched, e.g. "World Cup") or an external id ("lg_…"). limit: max fixtures to return (1–200, default 50). timezone: optional IANA timezone (e.g. "America/New_York", "Asia/Shanghai") to render each fixture's kickoff in its ``summary`` as local time; default UTC.
    Connector
  • List the fixtures for a calendar day — or a bounded [date, date_to] range. Unlike list_today_matches (today + anything still live), this is a strict window for whatever ``date`` you ask for. Pass ``date_to`` (inclusive, max 31 days after ``date``) to cover a whole tournament window in ONE call — "all group-stage matches June 11–28" needs no per-day loop. UTC is canonical: pass an IANA ``timezone`` and the day boundaries are computed in that zone (so "June 12 in Shanghai" excludes a match that is still June 11 / already June 13 locally); each fixture keeps its UTC ``scheduled_at`` and adds ``scheduled_at_local``. Capped to ``limit`` (``truncated`` flags overflow) — narrow with sport/status/league rather than paging. Args: date: REQUIRED calendar day "YYYY-MM-DD" (e.g. "2026-06-12") — the window start. date_to: optional inclusive end day "YYYY-MM-DD" (max 31 days after ``date``); omit for a single day. timezone: optional IANA timezone (e.g. "Asia/Shanghai", "America/New_York") for the day boundary; default is the UTC day. sport: optional filter — "football" or "basketball". status: optional filter — "scheduled", "live" or "finished". league: optional league filter — a name (fuzzy-matched, e.g. "World Cup") or an external id ("lg_…"). limit: max fixtures to return (1–200, default 50).
    Connector
  • Look back at finished-match scores from the 30-day results cache, most-recent-first. Results-only: each entry is the final score, red cards and finished time (no odds). Unlike the live tools, these survive a restart — use it for "what was the score of X?" or "yesterday's results". Args: date: optional UTC kickoff date "YYYY-MM-DD" — the day the match was played. team: optional case-insensitive substring matched against either team name. league: optional case-insensitive substring matched against the league name. limit: max results to return, most-recent-first (1–200, default 50).
    Connector
  • List events (schedules and live scores), paginated by id (after_id). Filter by sport, league, status, date range, season, or team_id (resolve teams via list_teams / get_team). Returns event id, name, sport/league, start time, status, and venue for each; pass include_scores to also inline participants + scores (intended for small result sets — use get_event for one event's full detail, or query_events for free-text/natural-language filters instead of structured params).
    Connector
  • Get AI bet intelligence for an event. bets[] comes in two shapes — branch on the presence of probability (probability model) vs. confidence_score (points model). Probability model, currently soccer/MLS only: bets carry probability/interval/p_model/p_market/blend_w/fair_price/edge/sufficiency/phase/model_version/drivers and no confidence_score, coverage, signals, or validator. probability is calibrated and sums to 1 across a market's outcomes; p_market is the de-vigged market price, which you cannot recompute from a single price. Where no fitted model has cleared out-of-sample validation for a league, blend_w is 0, probability equals p_market, and p_model/edge/tier are null — a probability taken from the market has no honest edge against the price it came from; treat those events as fair-price reference, not as picks. drivers is normally empty then; Stage 6 Match Context drivers (soccer.match_context.*) may still cite the Fact Ledger with effect 0. Points model, every other sport/league: confidence scores, signal breakdowns, rationale, and narratives per bet. Signal keys (signal_serve_rtn, signal_surface, etc.) are shared across sports but mean different things per sport (for soccer signal_serve_rtn is Attack/Defense Edge, not tennis Serve/Return) — for NFL, NCAAF, and points-model soccer leagues, bets[].signals._labels maps each present signal_* key to its sport-specific label; prefer rationale/attribution for prose when you don't need raw scores. Both shapes include event-level analyst_take and match_overview. Match-level tokens (OVER, UNDER, ML_DRAW) have null player_role/player_id/team_id/player_name, so summing exposure by team_id never double-counts a draw. bookmaker defaults to pinnacle and is a no-op for probability-model sports, which report the book their assessment was priced against. Returns available:false with no charge if intelligence hasn't been computed yet for this event/bookmaker.
    Connector
  • Return today's games that have player props available for a sport. Read-only. No side effects. Requires an API key; rate-limited per your tier. Returns: { sport, count, games: Array<{ id, sport, homeTeam, awayTeam, startTime, live, source }> }. id is the eventId to pass to get_game_props (prefixed ud- for Underdog or bv- for Bovada); live is true when the game is in progress; source is "underdog" or "bovada". Live games sort first; scheduled games follow. Typical workflow: call list_games to discover eventIds, then pass an eventId to get_game_props. If sport is omitted the server selects the active in-season league automatically. Returns count=0 with an empty games array (not an error) when no props are posted yet for the day. When to use: to browse all games on the slate or to find an eventId before calling get_game_props. When not to use: if you already have the eventId, skip this and call get_game_props directly. Use find_game instead when you know the team names but want a single-game eventId without browsing the full slate.
    Connector
  • Call this when the user asks about the activity, health, leaderboard, mood, or trends of a specific Telegram group tracked by Limzo. `slug` is the last part of the group's public page URL, limzo.com/s/<slug> (e.g. "hipo"). Returns the curated limzo.public_stats/v1 JSON: messages, replies, active members, daily series, top members, mood, reactions, language mix, the Limzo Levels ladder (lifetime XP + badge tiers), and weekly-league standings when the group has the league enabled. Optional `range`: 7d (default), 30d, all — the wider ranges only serve real data for groups on a paid plan and otherwise silently fall back to 7d, so check `range.key` in the result. Never includes verbatim member messages.
    Connector
  • Refresh connected fantasy leagues by asking Flaim to rediscover leagues through connected ESPN, Yahoo, and Sleeper accounts. Use only when the user explicitly asks to refresh or after the user presses the widget refresh button. This is non-destructive, but repeated refreshes can update Flaim registry timestamps and provider metadata; it does not change provider lineups or rosters, add or drop players, submit waiver claims or trades, or modify league settings. If this call succeeds, call get_user_session again to show the updated league list. If it fails, follow the error retry guidance and any retry_after value; do not retry in a loop.
    Connector
  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
    Connector
  • Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.
    Connector