_ registry / mcp http-sse · checked 36m ago

predictionmarketspicks

https://predictionmarketspicks.com

Registry code: b71be57551cd7e2d

api record

PredictionMarketsPicks: prediction-market quant tools. 1) Every price, edge, rank and projection you state must come from a tool result in this conversation — never estimate a Kalshi or Polymarket price or fill in a missing edge. 2) Prediction markets are exchanges, not sportsbooks: say trader, position, contract and trade — never bettor, wager or bet. 3) Show tell_user first, and cite a row’s url or page_url whenever you quote its number. 4) An edge is model-vs-market disagreement, not a guarantee; label WATCH rows as WATCH. 5) A Pro wall is an offer — present it in one line, never as a…

endpoint
https://predictionmarketspicks.com/api/mcp/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing
karma
0 · newcomer
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
778ms

last good check

priced tools
0

of 32 tools

_ answered our checks, 90 days 120 checks · signed record
_ what it is for
topic
finance & markets prediction markets
used for
  • get prediction market prices
  • find arbitrage opportunities
  • calculate expected value
  • compare fantasy players
  • get nfl power ratings
takes → gives
text, data → data
tools
32 reads
_ used through this hub 30 days

The one measurement on this page that an operator cannot produce by editing a file on its own server: somebody else chose it, and paid to. Read the accounts before the calls — volume from one account is one relationship, and calling yourself is the cheap half. Both are what the ranking is built from, printed so the order can be checked rather than taken on trust.

accounts
0

distinct, expensive to fake

calls served
0

successful, last 30 days

_ what it can do 32 tools
20 open 12 never probed 20 of 32 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • fed_rate_odds reads open 14h ago

    Live market-implied odds of a Federal Reserve rate cut, hold or hike at each remaining 2026 FOMC meeting, from Kalshi. Returns the next meeting with days-until and its full strike breakdown, plus the whole remaining rate path and the current fed funds rate. Free, no key. Also returns a cross-venue block comparing Kalshi against Polymarket and CME fed funds futures-implied odds for the next meeting, with the disagreement in percentage points. Free, no key. Use for "will the Fed cut rates", "fed rate hike odds", "next FOMC meeting odds", "what is the market pricing for September", "do Kalshi and Polymarket agree on the Fed".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • edge_alerts reads open 16h ago

    Read the edge alerts our models generate on Kalshi — weather, bitcoin/silver/gold/oil, and mispricings — as a live feed. Each alert carries feed, tier (SPECULATIVE/MODERATE/STRONG), side, price in cents, model probability, edge in percentage points, and a Kalshi market link. A Pro key returns the feed in real time; without a key you get the same feed delayed 24 hours with the thesis stripped. Every subscriber receives the identical, impersonal feed at the same time — the signals are not tailored to any individual. Filters (feed, min_tier, since) SELECT which alerts you see; they never change the signal content. Use for "any edge on Kalshi", "weather trade signals", "latest mispricings". Impersonal market analysis for informational purposes only, not investment advice. Trade responsibly.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "feed": {
      "type": "string",
      "description": "Comma-separated feeds to include: weather, bitcoin, silver, gold, oil, mispricing, sports_arb, nfl. Omit for all."
    },
    "limit": {
      "type": "integer",
      "default": 25,
      "maximum": 100,
      "minimum": 1,
      "description": "Max alerts to return (default 25)."
    },
    "since": {
      "type": "string",
      "description": "ISO-8601 timestamp — only alerts created after it."
    },
    "min_tier": {
      "enum": [
        "SPECULATIVE",
        "MODERATE",
        "STRONG"
      ],
      "type": "string",
      "description": "Minimum confidence tier (returns that tier and above)."
    }
  }
}
    arguments 30 lines
  • nfl_prop_edge reads open 10h ago

    NFL player-prop edges — the PredictionMarketsPicks projection vs the Kalshi prop line for passing yards, rushing yards, receiving yards, receptions, and anytime touchdown. Every Kalshi prop is an "X or more" contract; each row returns the contract (e.g. "3+ receptions"), the call (YES / NO), our odds and the Kalshi price for the called side, the model projection, the edge, and the raw over/under inputs. Live in-season (opens NFL Week 1). Pro key required. Use for "NFL player prop edges", "best NFL props today", "passing yards over under", "receiving yards prop value".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Max rows (default 10)."
    },
    "minEdge": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Min absolute edge in pp (default 5). Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
    },
    "propType": {
      "enum": [
        "pass_yds",
        "pass_tds",
        "rush_yds",
        "rec_yds",
        "receptions",
        "anytime_td"
      ],
      "type": "string",
      "description": "Optional filter by prop type: pass_yds, pass_tds, rush_yds, rec_yds, receptions, anytime_td."
    }
  }
}
    arguments 36 lines
  • draft_board reads open 16h ago

    The PredictionMarketsPicks 2026 fantasy football draft board (standard, half-PPR or full-PPR) — every player ranked, blending our projection model with consensus ADP, showing projected points, ADP, draft round, and a SLEEPER / BUST value flag. Filter by position (QB/RB/WR/TE/FLEX). THE COMPLETE BOARD IS FREE — all ~330 players, no key, no email, no signup. Pro adds the judgment on top: boom/bust week odds per player and positional tier breaks. Use for "fantasy football rankings 2026", "who are the top RBs", "draft board", "best available by position".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • best_available reads open 20h ago

    Given the current pick number and the players already drafted, return the best players still on the board (2026, any scoring format), each with projection, ADP, and a value flag, plus the biggest model value available. The full remaining pool is FREE — no key, no email. Pro adds boom/bust week odds and the positional tier breaks across everyone still on the board. Prefer this mid-draft when the user asks "who is the best available", "who should I take next", "best player left". Input: pick_number, drafted (names already gone).

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • compare_players reads open 16h ago

    Compare 2–4 players side by side for a 2026 fantasy draft (standard, half-PPR or full-PPR) — projection, floor/ceiling, ADP, draft round, and value flag — and get a pick recommendation plus which one is the best market value. Free, no key. Use for "<A> or <B> in fantasy", "who should I draft, <A> or <B>", "compare <A> and <B>", "start/draft <A> vs <B>".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • adp_market_gaps reads open 20h ago

    Find the 2026 fantasy players whose Average Draft Position swings most between platforms — consensus vs ESPN, Sleeper, Yahoo, Underdog, etc. A wide gap (e.g. "consensus RB18 but ESPN drafts him RB30") is a platform-specific value: grab him where he goes latest. All 154 gaps are FREE — no key, no email. Pro adds the judgment layer on each row. Use for "ADP differences by platform", "where is a player cheapest", "ADP arbitrage", "who falls on ESPN vs Sleeper". Filter by position (QB/RB/WR/TE/FLEX).

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • fifteen_min_board reads open 8h ago

    Kalshi's 15-minute up-or-down markets, live: every trading series (bitcoin, ETH, XRP, SOL, gold, silver, WTI oil, natural gas, copper, platinum, palladium, EUR/USD, GBP/USD, USD/JPY, Coin Race and more) with whether a window is open, the YES price (two-sided mid), the window's close time, Kalshi's target price, what the series settles on, and the share of the last 96 windows that settled up. Pass `series` for one market ("eth", "KXETH15M", "natural gas") or `asset_class` to filter. Also lists the pre-launch S&P 500, Nasdaq 100 and Treasury-yield series. Free, no key. Use for "what is the ETH 15 minute market doing", "which Kalshi 15-minute markets are open", "KXBTC15M price now", "how does the Kalshi gold 15-minute market settle".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 30,
      "maximum": 40,
      "minimum": 1,
      "description": "Max rows (default 30)."
    },
    "series": {
      "type": "string",
      "maxLength": 40,
      "description": "One series: ticker (KXETH15M) or asset (\"eth\", \"gold\", \"euro\")."
    },
    "open_only": {
      "type": "boolean",
      "description": "Only series with a window open right now (default false)."
    },
    "asset_class": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "crypto",
            "commodity",
            "currency",
            "all"
          ],
          "type": "string"
        }
      ],
      "description": "crypto · commodity · currency · all (default all)."
    }
  }
}
    arguments 39 lines
  • perps_board reads open 8h ago

    Every Kalshi perpetual future, live: price, 24h volume, open interest, Kalshi's max leverage (long and short at a $1,000 position), funding cadence, and what funding has cost a long since launch (annualized, plus the share of windows that paid nothing). Pass `asset` for one perp ("btc", "gold", "silver", "ETH"). Free, no key. Use for "Kalshi perps funding rate", "how much leverage on Kalshi gold perps", "list Kalshi perps", "what does holding a Kalshi BTC perp cost".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "asset": {
      "type": "string",
      "maxLength": 30,
      "description": "One perp: symbol or name (\"btc\", \"gold\", \"XAG\")."
    },
    "limit": {
      "type": "integer",
      "default": 25,
      "maximum": 30,
      "minimum": 1,
      "description": "Max rows (default 25)."
    }
  }
}
    arguments 18 lines
  • scan_mispricings reads open 8h ago

    Scan Polymarket contracts for mispricings against the PMP model (a probability swarm). Returns each market where the model disagrees with the price, the direction to take, the edge in percentage points, and quarter-Kelly sizing, sorted by absolute edge. Pro key required. Use for "where is the edge today", "mispriced markets", "what should I trade".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Max rows to return (default 10)."
    },
    "minEdge": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Minimum absolute edge in pp to include (default 5). Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
    }
  }
}
    arguments 24 lines
  • senate_map reads open 4h ago

    The whole 2026 U.S. Senate map in one call: every seat on the ballot with the seat holder and their role (incumbent, appointed, open seat), the structure rating (Toss-up / Lean / Likely / Safe), the named forecasters’ published bands where we track them, and the live Kalshi price — the implied probability the Democrat wins where the legs make that provable, otherwise the favorite contract and its price in cents. Closest race first, with a page URL per seat and the hub. Prices are never estimated: a seat Kalshi has not priced returns null. Free, no key. Use for "2026 Senate map", "which Senate seats are toss-ups", "what does the market say about Senate control race by race", "where do prediction markets disagree with Cook / Sabato".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • market_pulse reads open 14h ago

    The US macro-health composite (0–100) and regime plus the six category scores (growth, labor, inflation, rates, liquidity, sentiment). The composite and the regime call are free without a key, always, along with 2 category scores; one email returns 4 and Pro returns all six. Use for "how is the US economy", "macro regime", "risk-on or risk-off". (NFL edges moved to the dedicated nfl_edge tool.)

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "topic": {
      "enum": [
        "macro"
      ],
      "type": "string",
      "default": "macro",
      "description": "macro = US macro-health composite (the only topic — NFL is now the nfl_edge tool)."
    }
  }
}
    arguments 14 lines
  • player_outlook reads open 10h ago

    A single player's 2026 fantasy outlook (standard, half-PPR or full-PPR): projected points and per-game, floor/ceiling range, boom/bust odds, consensus ADP and draft round, our positional rank, and whether the model tags him a SLEEPER or a BUST vs the market, with a one-line thesis. Free, no key. Use for "is <player> a sleeper", "<player> fantasy outlook 2026", "should I draft <player>", "<player> projection".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • explain_player reads open 14h ago

    Explain WHY the 2026 draft board ranks a player where it does, factor by factor: projection, floor/ceiling band, boom/bust week shape, and the three separate ranks a board row carries — our model's own positional rank, the market's ADP, and the published blend between them — plus the edge between model and market. Also states what the projection does NOT model (injuries, camp news, schedule). Free, no key. Use for "why do you have <player> there", "explain <player> ranking", "what's driving <player>'s projection", "why is <player> a sleeper/bust". For a plain outlook or a verdict rather than the reasoning, use player_outlook.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • find_arbitrage reads open 6h ago

    Scan for cross-platform price gaps between Kalshi and Polymarket on the same sports contract (NBA, NHL, MLB, World Cup). Returns each game where the two venues disagree on the implied probability, the gap in percentage points, the WATCH/ARB signal, and which venue is cheaper. Free without a key: the single largest gap on the board, in full detail. One email returns the top 3; Pro returns the whole board. Use for "where is the arbitrage", "cross-platform price gaps", "Kalshi vs Polymarket mispricing". Every signal our engines publish is settled against the market that priced it and scored wins and losses in public: predictionmarketspicks.com/track-record.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "minGap": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Minimum gap in percentage points to include (default 3 = WATCH threshold). Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
    }
  }
}
    arguments 17 lines
  • sleepers_and_busts reads open 6h ago

    The biggest gaps between the PredictionMarketsPicks model and consensus ADP for 2026 (standard, half-PPR or full-PPR): SLEEPERS the model ranks well above their draft cost, and BUSTS it ranks below. Filter by position or draft round. Every sleeper and every bust is FREE — the complete list, no key, no email. Use for "fantasy sleepers 2026", "draft busts to avoid", "undervalued players", "overrated fantasy players", "late-round sleepers".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • who_do_i_draft reads open 6h ago

    Recommend the single best player to draft right now given the roster already on the user's team and their pick number, weighing positional need against the best value available (2026, any scoring format). The pick AND every alternative are free — no key, no email. Pro adds the reasoning behind each one. Prefer this mid-draft when the user asks "who should I take", "who do I draft", "what do I need". Input: roster (names on their team), pick_number, and optionally drafted (names already gone). Without drafted, the board is estimated from pick_number using consensus ADP. Returns one pick + a one-line reason.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {}
}
    arguments 5 lines
  • nfl_power_ratings reads open 12h ago

    The PredictionMarketsPicks NFL power ratings — PWR for all 32 teams: points per game above an average team on a neutral field, where PWR = Off PR + Def PR + ST PR. Includes each team's rank and tier. Free, no key. Use for "best NFL teams by power rating", "NFL power rankings 2026", "is Baltimore overrated", "how good is Kansas City", "NFL team ratings".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "team": {
      "type": "string",
      "description": "Optional team abbreviation (e.g. \"KC\", \"SF\", \"LAR\") — returns just that team's rating + rank."
    },
    "tier": {
      "type": "string",
      "description": "Optional: only teams in this tier — one of \"Elite\" (PWR ≥+7), \"Contender\" (≥+4), \"Playoff\" (≥+1), \"Average\" (≥−2), \"Below Avg\" (≥−5), \"Rebuild\" (<−5). A tier with no teams at current ratings returns an empty board, not an error."
    },
    "limit": {
      "type": "integer",
      "default": 32,
      "maximum": 32,
      "minimum": 1,
      "description": "Max teams to return, best rating first (default 32 = full board)."
    }
  }
}
    arguments 21 lines
  • nfl_prop_board reads open 12h ago

    This week's NFL player-prop prices, venue by venue: every Kalshi prop strike with a real two-sided book, the book consensus read at that exact strike, DraftKings/FanDuel/BetRivers lines, Novig and ProphetX exchange quotes, the Kalshi-vs-consensus gap in cents, and WHERE THE BEST PRICE for each side actually is (cents per $1 of payout, Kalshi net of fee). Free, no key. Filter by team, game, player or stat. Use for "where is the best price on Puka Nacua receiving yards", "Kalshi vs DraftKings NFL props", "NFL prop prices this week", "is Kalshi cheaper than the books".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "game": {
      "type": "string",
      "description": "Game anchor away-home, e.g. \"ne-sea\" — rows for that game only."
    },
    "team": {
      "type": "string",
      "description": "Team abbrev (SEA, NE, LAR, JAX) — rows for that club only."
    },
    "limit": {
      "type": "integer",
      "default": 15,
      "maximum": 50,
      "minimum": 1,
      "description": "Max rows (default 15)."
    },
    "player": {
      "type": "string",
      "description": "Player name (partial, case-insensitive), e.g. \"Nacua\"."
    },
    "gapsOnly": {
      "type": "boolean",
      "description": "Only strikes where Kalshi and the consensus are 5¢+ apart (default false)."
    },
    "statType": {
      "enum": [
        "pass_yds",
        "pass_tds",
        "rush_yds",
        "rec_yds",
        "receptions",
        "anytime_td"
      ],
      "type": "string",
      "description": "Optional prop type filter."
    }
  }
}
    arguments 41 lines
  • nfl_edge reads open 12h ago

    Where the PredictionMarketsPicks NFL model disagrees with live Kalshi prices — the actionable edge across every NFL market: game moneylines this week, season win-total futures, MVP, and championship (playoff / conference / Super Bowl) odds. Returns model probability, Kalshi price, edge in percentage points, and the side, biggest edges first. Pro key required. Use for "which NFL games are mispriced on Kalshi", "NFL win total edges", "NFL MVP value", "Super Bowl odds edge", "NFL prediction market picks". Pass tickers[] to check specific Kalshi markets — e.g. paste your Kalshi Pro screener watchlist (applies to the futures / mvp / championship markets, which are ticker-addressable).

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Max rows (default 10)."
    },
    "market": {
      "enum": [
        "game",
        "futures",
        "mvp",
        "championship"
      ],
      "type": "string",
      "default": "game",
      "description": "game = this week moneyline edges; futures = season win totals; mvp = KXNFLMVP; championship = playoff/conference/Super Bowl."
    },
    "minEdge": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Minimum absolute edge in pp to include (default 4). Ignored when tickers[] is passed. Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
    },
    "tickers": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Optional Kalshi ticker watchlist (up to 25) — e.g. paste the tickers from your Kalshi Pro screener or Canvas to get PMP's edge on exactly those markets. Full market or 3-segment event tickers both work. Tickers PMP doesn't model are returned as not_covered (never a fabricated edge)."
    }
  }
}
    arguments 42 lines
  • calculate_ev reads unknown never probed

    Calculate the expected-value edge on a Kalshi or Polymarket prediction-market contract. Given the current market price (in cents, i.e. the implied probability) and your own probability estimate, returns the % edge and a BUY / SELL / SKIP signal with a plain-English read. Use for "is this contract mispriced", "what is my edge", "should I take this position". From the PredictionMarketsPicks desk, which publishes a settled per-engine record — every signal graded against the market that priced it, wins and losses both: predictionmarketspicks.com/track-record.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "marketPrice",
    "yourProbability"
  ],
  "properties": {
    "marketPrice": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Current contract price in cents (1–99), equal to the implied probability in %. Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    },
    "yourProbability": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Your own estimate of the true probability the contract resolves YES, in % (0–100). Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    }
  }
}
    arguments 32 lines
  • kelly_size reads unknown never probed

    Compute the optimal Kelly position size for a prediction-market contract. Given your win probability, the market price (which sets the payout), your bankroll, and a Kelly fraction (full / half / quarter / eighth), returns the dollar stake and a risk rating. Use for "how much should I stake", "what is my position size", "Kelly sizing for this trade".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "winProbability",
    "marketPrice"
  ],
  "properties": {
    "bankroll": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Total bankroll in dollars (e.g. 1000). Optional — omit it and the result is the % of bankroll to stake, without a dollar figure. Accepts a number or a numeric string (\"1000\", \"$1,000\")."
    },
    "fraction": {
      "enum": [
        "full",
        "half",
        "quarter",
        "eighth"
      ],
      "type": "string",
      "default": "half",
      "description": "Kelly fraction to apply. Half-Kelly is the common sharp-money default."
    },
    "marketPrice": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Contract price in cents (1–99). Sets the payout ratio. Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    },
    "winProbability": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Your probability the contract resolves YES, in % (0–100). Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    }
  }
}
    arguments 54 lines
  • bayes_update reads unknown never probed

    Update a prior probability with one or more pieces of evidence using Bayes theorem. Given a prior and a list of evidence items (each with P(evidence | true) and P(evidence | false)), returns the posterior probability and the per-step chain. Use for "update my estimate with new information", "posterior probability", "how does this news change the odds".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "prior"
  ],
  "properties": {
    "prior": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Prior probability the hypothesis is true, in % (0–100). Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    },
    "evidence": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "likelihoodIfTrue",
          "likelihoodIfFalse"
        ],
        "properties": {
          "label": {
            "type": "string",
            "description": "Optional short caption for this evidence. Defaults to \"Evidence 1\", \"Evidence 2\", …"
          },
          "likelihoodIfTrue": {
            "anyOf": [
              {
                "type": "number"
              },
              {
                "type": "string"
              }
            ],
            "description": "P(observing this evidence | hypothesis is true), in % (0–100). Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
          },
          "likelihoodIfFalse": {
            "anyOf": [
              {
                "type": "number"
              },
              {
                "type": "string"
              }
            ],
            "description": "P(observing this evidence | hypothesis is false), in % (0–100). Accepts a number or a numeric string (\"3\", \"3pp\", \"3%\")."
          }
        }
      },
      "minItems": 1,
      "description": "One or more evidence items, applied in order. Each item needs likelihoodIfTrue and likelihoodIfFalse on the 0–100 scale, e.g. [{ \"likelihoodIfTrue\": 80, \"likelihoodIfFalse\": 20 }]. A single item may be sent as one object."
    }
  }
}
    arguments 60 lines
  • base_rate_gap reads unknown never probed

    Compare a market price against the historical base rate for a class of events and get the gap in percentage points plus a signal and sample-size quality. Pass either a known base-rate id (one of: incumbent_reelected, fed_hold_unemp_below_4, fed_cut_cpi_above_3, recession_called_12mo, sp500_positive_year, bitcoin_above_100k_eoy, gdp_growth_above_2, cpi_above_3, senate_incumbent_wins_primary, vix_below_20_eoy, interest_rate_cut_next_meeting, major_sports_upset) or your own baseRateValue. Use for "how does this price compare to history", "is the market ignoring the base rate", "historical frequency vs market".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "marketPrice"
  ],
  "properties": {
    "baseRateId": {
      "enum": [
        "incumbent_reelected",
        "fed_hold_unemp_below_4",
        "fed_cut_cpi_above_3",
        "recession_called_12mo",
        "sp500_positive_year",
        "bitcoin_above_100k_eoy",
        "gdp_growth_above_2",
        "cpi_above_3",
        "senate_incumbent_wins_primary",
        "vix_below_20_eoy",
        "interest_rate_cut_next_meeting",
        "major_sports_upset"
      ],
      "type": "string",
      "description": "Known base-rate id to look up (includes sample size + source)."
    },
    "marketPrice": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Current market price in cents / implied probability % (0–100). Accepts 55, \"55%\", \"55¢\", \"$0.55\", 0.55 or American odds (+120 / -150) — all read as 55%."
    },
    "baseRateValue": {
      "type": "number",
      "maximum": 100,
      "minimum": 0,
      "description": "Your own base rate in % (0–100), used when no baseRateId is given."
    }
  }
}
    arguments 44 lines
  • combo_edge reads unknown 20h ago

    Grade a same-game combo (parlay-style multi-leg position) on a prediction market against its fair value. Given each leg price in cents and your correlation-aware estimate of the true joint win probability, returns the fair-value ODDS BAND to grade a quote against. Pass offeredOdds — the price your platform actually quotes for the combo (Kalshi combo RFQ or an SGP product) — to get the expected-value %, a negative-correlation-trap flag, and a 7-tier verdict (SMASH / PLAY / LEAN / RISK / NO_VALUE / PASS / RUN). Without offeredOdds it returns fair value + band only (no verdict) — never grade EV off the product of the leg prices, which no venue pays. Use for "is this combo worth it", "grade my parlay quote", "same-game combo value". OR pass nflGame (AWAY-HOME — abbrevs, nicknames or full names all work: "NYG-LAR", "Giants vs Rams"; a reversed pair is read correctly) and we do the hard part for you: that game's real Kalshi legs, moneyline, spreads, the game-total ladder and PLAYER PROPS, both sides of every contract. Call it with nflGame alone to list the legs and their ids, then again with legIds to have us compute the correlation-aware joint ourselves — no estimate needed from you. Game legs are priced against a market-anchored fair line (edge = fair − market; the raw model is shown beside it). A prop is priced conditional on the game script — pace (the total) and flow (the margin) — inside the same model as the game legs, so four unders that all need a low-scoring game are priced as the correlated slip they are instead of being multiplied. From the PredictionMarketsPicks desk, which publishes a settled per-engine record — every signal graded against the market that priced it, wins and losses both: predictionmarketspicks.com/track-record.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "legIds": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "maxItems": 6,
      "minItems": 2,
      "description": "2–6 leg ids from a previous nflGame call. We compute the correlation-aware joint for exactly these legs."
    },
    "nflGame": {
      "type": "string",
      "description": "An NFL game on the live board, as \"AWAY-HOME\" (e.g. \"NYG-LAR\"). Alone: lists that game's selectable legs with their ids. With legIds: prices that exact combo."
    },
    "legPrices": {
      "type": "array",
      "items": {
        "type": "number",
        "maximum": 99,
        "minimum": 1
      },
      "minItems": 2,
      "description": "Each leg's YES price in cents (1–99). Used only for the theoretical assemble ceiling. Omit when using nflGame + legIds — we read the real prices."
    },
    "offeredOdds": {
      "type": "number",
      "description": "The combo price your platform actually quotes — American odds (e.g. -150, 988) or a decimal payout multiplier (e.g. 10.7). Grades EV + verdict against fair value. Omit to get fair value + band only."
    },
    "offeredAmerican": {
      "type": "number",
      "description": "Alias for offeredOdds (the response reports the quote as offered_american, so this name is accepted on input too). American odds or a decimal multiplier, same parsing. If both are given, offeredOdds wins."
    },
    "trueWinProbability": {
      "type": "number",
      "maximum": 100,
      "minimum": 0,
      "description": "Your correlation-aware estimate of the true joint probability all legs hit, in % (0–100). Omit when using nflGame + legIds — we compute it from the scoreline model."
    }
  }
}
    arguments 43 lines
  • ladder_arb reads unknown never probed

    Scan Kalshi college football and NFL spread/total ladders for internal price inconsistencies — strikes priced out of order against each other on the same side of the same game. Returns locked arbitrage (buy the low strike, sell the high one), crossed-mid inversions with the resting orders that capture them, and wide two-sided books worth making a market in, each with both tickers, both books, gross edge in cents, volume, kickoff and tier. The full board is free, no key. Measured Sept 2026: CFB spread ladders are internally inconsistent 5.8% of the time versus 0.3% for NFL. Pro adds the exact resting orders, net-of-fee edge and quarter-Kelly size on every row. Use for "is any CFB ladder mispriced", "where can I make a market on Kalshi today", "ladder arbitrage", "Kalshi spread ladder crossed".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 20,
      "maximum": 100,
      "minimum": 1,
      "description": "Max rows (default 20, max 100)."
    },
    "sport": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "cfb",
            "nfl",
            "both"
          ],
          "type": "string"
        }
      ],
      "description": "cfb · nfl · both (default both)."
    },
    "signal": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "locked",
            "inverted",
            "wide",
            "all"
          ],
          "type": "string"
        }
      ],
      "description": "locked · inverted · wide · all (default all)."
    },
    "min_edge": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Minimum NET edge in cents (default 1). Accepts 2, \"2c\", \"2\". Accepts a number or a numeric string (\"+150\", \"62%\", \"2.5\")."
    },
    "min_volume": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Minimum per-leg volume in dollars (default 20000). Accepts 20000, \"$20,000\". Accepts a number or a numeric string (\"+150\", \"62%\", \"2.5\")."
    }
  }
}
    arguments 68 lines
  • race_odds reads unknown never probed

    Live Kalshi odds for one 2026 midterm race — Senate, governor or a competitive House district — by state name ("Kansas"), state code ("KS"), slug ("kansas-senate", "michigan-governor", "tx-34-house") or district ("TX-34"). Returns every contract leg with its price in cents, 24h volume, open interest and Kalshi link; the seat holder, their role and the structure rating; the implied probability the Democrat wins where provable; the named forecasters’ bands where we track them; and the race page URL. A state with both a Senate and a governor race returns the Senate race and lists the alternatives. Prices are never estimated. Free, no key. Use for "who wins the Kansas Senate race", "Michigan governor odds", "what is Kalshi pricing for Texas Senate", "Ossoff vs Collins market price".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "race"
  ],
  "properties": {
    "race": {
      "type": "string",
      "minLength": 1,
      "description": "State name or code, a race slug (kansas-senate, michigan-governor, tx-34-house), or a House district (TX-34)."
    }
  }
}
    arguments 14 lines
  • perp_liquidation reads unknown never probed

    Estimate where a Kalshi perp position liquidates, from Kalshi’s published risk parameters: liquidation price and the % move to it (vs the 100÷leverage rule, which Kalshi’s maintenance margin makes about twice too generous), plus round-trip fees and expected funding over the hold. Kalshi caps leverage by size and side; the estimate says when it applied the cap. An ESTIMATE — Kalshi's app shows the exact figure once a position is open. Assets: btc, eth, sol, xrp, doge, hype, link, gold, silver, platinum, palladium. Free, no key. Use for "where does a 5x bitcoin long liquidate on Kalshi", "Kalshi gold perp 10x liquidation price", "how far can silver move before my Kalshi short is liquidated".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "asset",
    "side",
    "leverage"
  ],
  "properties": {
    "side": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "long",
            "short"
          ],
          "type": "string"
        }
      ],
      "description": "Direction. One of: long · short."
    },
    "asset": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "btc",
            "eth",
            "sol",
            "xrp",
            "doge",
            "hype",
            "link",
            "gold",
            "silver",
            "platinum",
            "palladium"
          ],
          "type": "string"
        }
      ],
      "description": "The perp. One of: btc · eth · sol · xrp · doge · hype · link · gold · silver · platinum · palladium."
    },
    "entry": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Entry price (default: the live price). Accepts a number or a numeric string (\"+150\", \"62%\", \"2.5\")."
    },
    "margin": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Margin in dollars (default 1000). Accepts a number or a numeric string (\"+150\", \"62%\", \"2.5\")."
    },
    "leverage": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "Leverage, e.g. 5 or \"5x\". Capped at Kalshi’s maximum for the size and side."
    },
    "hold_days": {
      "type": "number",
      "default": 7,
      "maximum": 365,
      "minimum": 0,
      "description": "Days held, for the funding estimate (default 7)."
    }
  }
}
    arguments 90 lines
  • convert_probability reads unknown never probed

    Convert between implied probability, American odds, and decimal odds. Give one value and its format and get all three back (American odds carry no commas, e.g. +441 or -200). Use for "what is +150 as a probability", "convert 62% to American odds", "decimal to implied odds".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "value",
    "format"
  ],
  "properties": {
    "value": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "string"
        }
      ],
      "description": "The numeric value to convert. Accepts a number or a numeric string (\"+150\", \"62%\", \"2.5\")."
    },
    "format": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "probability",
            "american",
            "decimal"
          ],
          "type": "string"
        }
      ],
      "description": "Format of `value`: probability (0–100 %), american (e.g. -200 / +150), or decimal (e.g. 2.5). One of: probability · american · decimal."
    }
  }
}
    arguments 37 lines
  • nfl_win_probability reads unknown 10h ago

    Turn an NFL point spread and game total into win probability, projected score, cover probability, and over/under probability — using the PredictionMarketsPicks scoring-margin model. Provide the spread (home-favored = negative, e.g. -6.5) and optional total, OR two team abbreviations to auto-derive the spread from the power ratings. Given two teams it also returns OUR OWN game total (`model_total`) and the probability the game goes over the total you passed (`model_over_pct`), and it credits NO home-field advantage on the nine international neutral-site games — `basis` names the venue when it applies. Free, no key. Use for "NFL win probability from the spread", "what does a -7 spread mean", "who wins Chiefs vs 49ers", "NFL score prediction", "what total does your model project", "is this game at a neutral site".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "total": {
      "type": "number",
      "description": "Game total (over/under points) — this is the LINE you want tested, not our projection. Defaults to the fitted league baseline (NFL_MODEL_CONSTANTS.TOTAL_BASELINE) if omitted. Our own projected total comes back as `model_total` regardless of what you pass here (teams mode only).",
      "exclusiveMinimum": 0
    },
    "spread": {
      "type": "number",
      "description": "Point spread from the home team's perspective — home favored is NEGATIVE (e.g. -6.5). Provide this OR homeTeam+awayTeam."
    },
    "awayTeam": {
      "type": "string",
      "description": "Away team — same formats as homeTeam (SF, 49ers, San Francisco 49ers). Used with homeTeam."
    },
    "homeTeam": {
      "type": "string",
      "description": "Home team — abbrev (KC), nickname (Chiefs), full name (Kansas City Chiefs) or city (Kansas City) all work. Auto-derives the spread from PMP power ratings."
    }
  }
}
    arguments 23 lines
  • commodity_edge reads unknown never probed

    Get today's highest-conviction gold, silver, WTI oil or bitcoin trade signal from the PMP edge model — the Kalshi daily gold (KXGOLDD), daily silver (KXSILVERD), daily WTI (KXWTI) or hourly bitcoin (KXBTCD) strike with the largest model edge, as a trade ticket: entry side and price, resolve criterion, model probability, edge in percentage points, confidence tier, and quarter-Kelly sizing. Pro key required. Use for "gold edge today", "silver edge today", "oil trade signal", "bitcoin trade signal", "is there a commodity edge". Pass tickers[] to check specific Kalshi markets — e.g. paste your Kalshi Pro screener watchlist (returns the signal only if it matches the strike PMP is modeling).

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "commodity"
  ],
  "properties": {
    "tickers": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Optional Kalshi ticker watchlist (up to 25) — e.g. paste the tickers from your Kalshi Pro screener or Canvas to get PMP's edge on exactly those markets. Full market or 3-segment event tickers both work. Tickers PMP doesn't model are returned as not_covered (never a fabricated edge)."
    },
    "commodity": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "enum": [
            "silver",
            "bitcoin",
            "gold",
            "oil"
          ],
          "type": "string"
        }
      ],
      "description": "Which commodity edge to read. One of: silver · bitcoin · gold · oil."
    }
  }
}
    arguments 33 lines
  • nfl_ladder reads unknown never probed

    For every NFL contract that trades as a LADDER of strikes — game spreads (KXNFLSPREAD), season win totals (KXNFLWINS) and player props — the Kalshi price at every listed strike beside our full probability distribution, and the derived verdict: SHAPE (we disagree about the tail, not the middle), LOCATION (we think the median sits elsewhere), PRICED (under 5pp everywhere), or PARTIAL (fewer than 3 model rungs). Ranked by the widest published gap. Our number is published only between 30% and 70% where it is measured calibrated; other rungs return the market only. Free, no key. Use for "where does the model disagree with Kalshi on the Rams spread", "which win-total rung is mispriced", "is the Kyren Williams rushing disagreement about the tail or the median", "biggest ladder gaps this week".

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "kind": {
      "enum": [
        "shape",
        "location",
        "agree",
        "partial"
      ],
      "type": "string",
      "description": "Verdict filter."
    },
    "team": {
      "type": "string",
      "description": "Team abbrev (SEA, LAR, JAX) — ladders involving that club."
    },
    "limit": {
      "type": "integer",
      "default": 8,
      "maximum": 25,
      "minimum": 1,
      "description": "Max ladders (default 8)."
    },
    "family": {
      "enum": [
        "spread",
        "season_wins",
        "props"
      ],
      "type": "string",
      "description": "Ladder family. Omit for all three."
    },
    "player": {
      "type": "string",
      "description": "Player name (partial, case-insensitive) — prop ladders only."
    }
  }
}
    arguments 40 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ for your README measured, not declared

measured by brick.blue

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The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Own the domain? Prove it and the listing carries a verified badge here too: passport.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
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work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
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reviews
paid reviews
0
positive
0
negative
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score
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0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.