_ registry / mcp streamable-http · checked 1h ago

Foresea

https://foresea.ink

Registry code: 05305b8419850262

api record

Foresea gives calibrated probabilities for any resolvable future event, with evidence and the edge vs prediction markets — and it publishes a resolved track record so you can see how right it's been. Use forecast for any yes/no question, analyze_market to evaluate a specific Polymarket/Kalshi market, scan_markets / edge_board to find mispriced markets, and track_record to gauge how much to trust a forecast before acting.

endpoint
https://foresea.ink/mcp/
protocol
streamable-http ·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
364ms

last good check

priced tools
0

of 21 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ 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 21 tools
21 never probed 0 of 21 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.

  • foresea_market_leaderboard unknown never probed

    Call this to fetch the top profitable prediction market trader leaderboard and rankings from Polymarket.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_market_leaderboardArguments",
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 20
    }
  }
}
    arguments 11 lines
  • foresea_forecast unknown never probed

    Call this whenever the user asks about probability, likelihood, or whether something will happen. Good triggers: "Will X happen?", "What are the chances of Y?", "How likely is Z?", "What's the probability that…", "Do you think X will…", "Should I bet on…". Returns a calibrated YES/NO probability (or numeric/date range) with written rationale and supporting news evidence. If you also have a market price (market_probability) or URL (market_url), pass it to get the model-vs-market edge — how mispriced the market is. Example: question="Will the Fed cut rates by March 2026?", market_probability=0.4 → {predicted_answer:"No", confidence:0.62, rationale, evidence_sources, market_analysis:{model_probability:0.54, edge:+0.14, stance:"model_above_market"}} Handles: binary YES/NO, multiple-choice, numeric ranges, and date questions.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_forecastArguments",
  "required": [
    "question"
  ],
  "properties": {
    "options": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "title": "Options",
      "default": null
    },
    "variant": {
      "type": "string",
      "title": "Variant",
      "default": "variant0_neutral_baseline"
    },
    "question": {
      "type": "string",
      "title": "Question"
    },
    "categories": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "title": "Categories",
      "default": null
    },
    "market_url": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Url",
      "default": null
    },
    "description": {
      "type": "string",
      "title": "Description",
      "default": ""
    },
    "question_type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Question Type",
      "default": null
    },
    "evidence_top_k": {
      "type": "integer",
      "title": "Evidence Top K",
      "default": 5
    },
    "market_outcome": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Outcome",
      "default": null
    },
    "attach_evidence": {
      "type": "boolean",
      "title": "Attach Evidence",
      "default": true
    },
    "market_platform": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Platform",
      "default": null
    },
    "market_probability": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Probability",
      "default": null
    },
    "resolution_criteria": {
      "type": "string",
      "title": "Resolution Criteria",
      "default": ""
    }
  }
}
    arguments 128 lines
  • foresea_analyze_market unknown never probed

    Call this when the user mentions a specific prediction market by URL, slug, or ticker — or asks whether a particular market is over/underpriced. Good triggers: "Is this Polymarket fair?", "What's the edge on kalshi:XXXXX?", "Should I buy/sell this market?", user pastes a Polymarket or Kalshi URL. Fetches the live price, gathers evidence, forecasts, computes model-vs-market edge, and returns a recommendation. Use foresea_forecast instead when there is no specific live market — just a general probability question. Example: platform="polymarket", slug="fed-rate-cut-march-2026" → {model_probability, market_probability, edge, stance, recommendation, thesis}.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_analyze_marketArguments",
  "properties": {
    "slug": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Slug",
      "default": null
    },
    "skills": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "object",
            "additionalProperties": {
              "type": "string"
            }
          }
        },
        {
          "type": "null"
        }
      ],
      "title": "Skills",
      "default": null
    },
    "ticker": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Ticker",
      "default": null
    },
    "variant": {
      "type": "string",
      "title": "Variant",
      "default": "variant0_neutral_baseline"
    },
    "platform": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Platform",
      "default": null
    },
    "question": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Question",
      "default": null
    },
    "market_id": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Id",
      "default": null
    },
    "tool_loop": {
      "type": "boolean",
      "title": "Tool Loop",
      "default": false
    },
    "builtin_skills": {
      "type": "boolean",
      "title": "Builtin Skills",
      "default": false
    },
    "evidence_top_k": {
      "type": "integer",
      "title": "Evidence Top K",
      "default": 5
    },
    "max_tool_steps": {
      "type": "integer",
      "title": "Max Tool Steps",
      "default": 5
    },
    "ground_in_record": {
      "type": "boolean",
      "title": "Ground In Record",
      "default": false
    },
    "market_probability": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Probability",
      "default": null
    }
  }
}
    arguments 126 lines
  • foresea_scan_markets unknown never probed

    Call this when the user wants to find mispriced or interesting markets, not evaluate a specific one. Good triggers: "What should I bet on?", "Find me trading opportunities", "Which markets are mispriced right now?", "What's Foresea's best edge today?", "Scan Polymarket for opportunities". Returns markets ranked by model-vs-market disagreement, each with model probability, market price, and edge. For a specific market, use foresea_analyze_market instead. Example: platform="kalshi", min_edge=0.1 → [{question, market_probability, model_probability, edge, market_url}].

    mcp-tool

    {
  "type": "object",
  "title": "foresea_scan_marketsArguments",
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 4
    },
    "query": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Query",
      "default": null
    },
    "min_edge": {
      "type": "number",
      "title": "Min Edge",
      "default": 0.1
    },
    "platform": {
      "type": "string",
      "title": "Platform",
      "default": "polymarket"
    },
    "evidence_top_k": {
      "type": "integer",
      "title": "Evidence Top K",
      "default": 3
    }
  }
}
    arguments 38 lines
  • foresea_batch_quotes unknown never probed

    Call this when the user wants current price/volume for several markets at once -- a watchlist, a portfolio, "check on these 5 markets" -- instead of calling foresea_analyze_market once per market. Each ref is "platform:ident", e.g. "kalshi:KXFED-25JUN-H" or "polymarket:some-market-slug". Every quote carries fetched_at and age_seconds so you can judge freshness yourself -- both venues rate-limit hard, so don't assume a quote is live without checking age_seconds. One bad ref returns an error on that entry only; the rest of the batch still succeeds. Up to 50 refs per call. Example: refs=["kalshi:KXFED-25JUN-H", "polymarket:fed-cut-2026"] → {quotes: [{platform, ident, probability, volume, fetched_at, age_seconds, error}], count, truncated}.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_batch_quotesArguments",
  "required": [
    "refs"
  ],
  "properties": {
    "refs": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Refs"
    }
  }
}
    arguments 16 lines
  • foresea_check_run unknown never probed

    Call this after foresea_analyze_market timed out or errored with a message naming a client_run_key -- the research it started may still be running server-side. Returns {"status": "running", ...} if it's not done yet (call again in a bit), or the full report once it is. Do not call this speculatively; only use the client_run_key a prior foresea_analyze_market call actually gave you. Example: client_run_key="a1b2c3..." → {status:"running", id:"agent_run_..."} or the full report once complete.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_check_runArguments",
  "required": [
    "client_run_key"
  ],
  "properties": {
    "client_run_key": {
      "type": "string",
      "title": "Client Run Key"
    }
  }
}
    arguments 13 lines
  • foresea_track_record unknown never probed

    Call this when the user asks how reliable or accurate Foresea is, or wants to know whether to trust a forecast. Good triggers: "How good is Foresea?", "What's the track record?", "Has it been right before?", "Is it calibrated?", "What's the Brier score?". Returns accuracy, Brier score, calibration (ECE), and skill-vs-market broken down by time horizon.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_track_recordArguments",
  "properties": {}
}
    arguments 5 lines
  • foresea_edge_board unknown never probed

    Call this when the user wants the current top trading opportunities with explicit trade directions and historical backing. Good triggers: "What are the best bets right now?", "Show me the edge board", "Which model is winning the paper-trading competition?", "What's the strongest edge today?", "Are these edges statistically significant?". Returns open markets ranked by model-vs-market disagreement, each with Buy YES/NO direction, implied odds, whether the edge is historically significant, and a multi-model comparison.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_edge_boardArguments",
  "properties": {}
}
    arguments 5 lines
  • foresea_venue_data unknown never probed

    Read public historical markets/candles/trades, batch books/midpoints/spreads, fees, holders, open interest, event volume, milestones and weather. Omit operation to discover operation names and schemas. No account or write access.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_venue_dataArguments",
  "properties": {
    "body": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "object",
            "additionalProperties": true
          }
        },
        {
          "type": "null"
        }
      ],
      "title": "Body",
      "default": null
    },
    "platform": {
      "type": "string",
      "title": "Platform",
      "default": ""
    },
    "operation": {
      "type": "string",
      "title": "Operation",
      "default": ""
    },
    "parameters": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "title": "Parameters",
      "default": null
    }
  }
}
    arguments 45 lines
  • foresea_orderbook unknown never probed

    Call this to fetch the live bids and asks orderbook depth for a Kalshi market ticker (e.g. 'KXFED-25JUN-H') or Polymarket YES-token ID.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_orderbookArguments",
  "required": [
    "ticker_or_token"
  ],
  "properties": {
    "platform": {
      "type": "string",
      "title": "Platform",
      "default": ""
    },
    "ticker_or_token": {
      "type": "string",
      "title": "Ticker Or Token"
    }
  }
}
    arguments 18 lines
  • foresea_market_tags unknown never probed

    Call this to sample Polymarket's category vocabulary. Each entry is a label and the slug that identifies it. This is one page of at most 100 tags, not the full taxonomy: Polymarket has tens of thousands, and the endpoint returns a fixed slice that is ordered neither alphabetically nor by market activity. So absence here does not mean a tag is unused, presence does not mean it is active, and some entries are one-off or misspelled. Treat it as a vocabulary sample, not a classification the markets are organised by.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_market_tagsArguments",
  "properties": {}
}
    arguments 5 lines
  • foresea_price_history unknown never probed

    Call this to retrieve historical price series or OHLC candlesticks for a market (e.g. Kalshi ticker or Polymarket token/slug).

    mcp-tool

    {
  "type": "object",
  "title": "foresea_price_historyArguments",
  "required": [
    "ticker_or_market"
  ],
  "properties": {
    "series_ticker": {
      "type": "string",
      "title": "Series Ticker",
      "default": ""
    },
    "ticker_or_market": {
      "type": "string",
      "title": "Ticker Or Market"
    }
  }
}
    arguments 18 lines
  • foresea_live_data unknown never probed

    Call this to fetch real-time sports game statistics, play-by-play data, and live event feeds from Kalshi. Provide event_ticker for event charts, or milestone_id with data_type="game_stats" for play-by-play.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_live_dataArguments",
  "properties": {
    "data_type": {
      "type": "string",
      "title": "Data Type",
      "default": ""
    },
    "event_ticker": {
      "type": "string",
      "title": "Event Ticker",
      "default": ""
    },
    "milestone_id": {
      "type": "string",
      "title": "Milestone Id",
      "default": ""
    }
  }
}
    arguments 21 lines
  • foresea_polymarket_meta unknown never probed

    Call this to fetch Polymarket metadata: event series listings, community discussion comments for a market, or sports league metadata (target: 'series', 'comments', 'sports', 'teams'). 'series' lists the series and how many events each holds, not the events themselves -- fetch a series by slug for those. 'sports' lists every league with the ids that link it to other tools, not league artwork or homepages. 'comments' gives the comment, its author address and its reaction count, not the commenters' profiles or individual reactions.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_polymarket_metaArguments",
  "properties": {
    "target": {
      "type": "string",
      "title": "Target",
      "default": "series"
    },
    "market_id": {
      "type": "string",
      "title": "Market Id",
      "default": ""
    }
  }
}
    arguments 16 lines
  • foresea_recent_trades unknown never probed

    Call this to fetch recent public executed trades / trade tape (prices, sizes, timestamps) on Kalshi or Polymarket.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_recent_tradesArguments",
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 20
    },
    "platform": {
      "type": "string",
      "title": "Platform",
      "default": "kalshi"
    },
    "ticker_or_token": {
      "type": "string",
      "title": "Ticker Or Token",
      "default": ""
    }
  }
}
    arguments 21 lines
  • foresea_debate_market unknown never probed

    Conduct an adversarial multi-agent debate (Bull vs. Bear vs. Chief Risk Judge) to cross-examine evidence and isolate blind spots on a forecasting question.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_debate_marketArguments",
  "required": [
    "question"
  ],
  "properties": {
    "platform": {
      "type": "string",
      "title": "Platform",
      "default": "Market"
    },
    "question": {
      "type": "string",
      "title": "Question"
    },
    "market_probability": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "title": "Market Probability",
      "default": null
    },
    "resolution_criteria": {
      "type": "string",
      "title": "Resolution Criteria",
      "default": ""
    }
  }
}
    arguments 35 lines
  • foresea_optimize_portfolio unknown never probed

    Calculate optimal mathematical Fractional Kelly capital allocations and position sizes across live Grade A/B prediction market opportunities.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_optimize_portfolioArguments",
  "properties": {
    "min_edge": {
      "type": "number",
      "title": "Min Edge",
      "default": 0.05
    },
    "bankroll_usd": {
      "type": "number",
      "title": "Bankroll Usd",
      "default": 1000
    },
    "kelly_fraction": {
      "type": "number",
      "title": "Kelly Fraction",
      "default": 0.25
    }
  }
}
    arguments 21 lines
  • foresea_feed_latest unknown never probed

    Fetch the real-time unified Foresea Alpha & Agent Feed, combining live prediction market edge signals, autonomous agent trades & theses, and leaderboard standings.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_feed_latestArguments",
  "properties": {
    "limit": {
      "type": "integer",
      "title": "Limit",
      "default": 10
    },
    "min_edge": {
      "type": "number",
      "title": "Min Edge",
      "default": 0.05
    }
  }
}
    arguments 16 lines
  • foresea_weather_radar unknown never probed

    Scan live temperature and weather prediction markets (Kalshi KXHIGHNY, KXHIGHCHI, KXHIGHMIA, KXHIGHAUS, KXHIGHDEN, KXHIGHPHIL, etc.) against neural weather models (Google DeepMind WeatherNext 3 / MetNet) and high-resolution multi-model ensembles, calibrated with station microclimate bias profiles. Returns ranked mispricings, strike bracket probabilities, and model-vs-market edge.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_weather_radarArguments",
  "properties": {
    "target_date": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Target Date",
      "default": null
    }
  }
}
    arguments 18 lines
  • foresea_weather_forecast unknown never probed

    Retrieve neural model weather forecasts (Google Maps Weather API / WeatherNext 3 / MetNet, ECMWF, GFS, GraphCast) with empirical station bias correction (e.g. KNYC Central Park, KMDW Chicago Midway, KDEN Denver) and strike bracket probability calculations for weather prediction markets.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_weather_forecastArguments",
  "required": [
    "station_or_query"
  ],
  "properties": {
    "target_date": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Target Date",
      "default": null
    },
    "station_or_query": {
      "type": "string",
      "title": "Station Or Query"
    }
  }
}
    arguments 25 lines
  • foresea_exchange_status unknown 1h ago

    Call this to check Kalshi exchange operational status (trading active flag) and operational hours/schedule.

    mcp-tool

    {
  "type": "object",
  "title": "foresea_exchange_statusArguments",
  "properties": {}
}
    arguments 5 lines
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_ how we know
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Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

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