此 MCP 可以做什么
Forecasts events, analyzes prediction markets, scans for market edges, and provides market data, weather forecasts, and portfolio allocation analysis.
功能
工具
28
工具
foresea_analyze_market
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}.
输入模式
{'type': 'object', 'title': 'foresea_analyze_marketArguments', 'properties': {'slug': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Slug', 'default': None}, 'skills': {'anyOf': [{'type': 'array', 'items': {'type': 'object', 'additionalProperties': {'type': 'string'}}}, {'type': 'null'}], 'title': 'Skills', 'default': None}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'variant': {'type': 'string', 'title': 'Variant', 'default': 'variant0_neutral_baseline'}, 'platform': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Platform', 'default': None}, 'question': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Question', 'default': None}, 'market_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Market Id', 'default': None}, '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': None}}}
输出模式
{'type': 'object', 'title': 'foresea_analyze_marketOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_batch_forecast
Submit up to 25 forecasting questions concurrently and receive structured predictions
with confidence probabilities, bull/bear factor decomposition, key catalysts, and evidence
citations for each question.
输入模式
{'type': 'object', 'title': 'foresea_batch_forecastArguments', 'properties': {'items': {'anyOf': [{'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}}, {'type': 'null'}], 'title': 'Items', 'default': None}, 'variant': {'type': 'string', 'title': 'Variant', 'default': 'variant0_neutral_baseline'}, 'questions': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Questions', 'default': None}, 'evidence_top_k': {'type': 'integer', 'title': 'Evidence Top K', 'default': 3}, 'attach_evidence': {'type': 'boolean', 'title': 'Attach Evidence', 'default': True}, 'concurrency_limit': {'type': 'integer', 'title': 'Concurrency Limit', 'default': 5}}}
输出模式
{'type': 'object', 'title': 'foresea_batch_forecastOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_batch_quotes
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}.
输入模式
{'type': 'object', 'title': 'foresea_batch_quotesArguments', 'required': ['refs'], 'properties': {'refs': {'type': 'array', 'items': {'type': 'string'}, 'title': 'Refs'}}}
输出模式
{'type': 'object', 'title': 'foresea_batch_quotesOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_cancel_order
Cancel an active open order on Kalshi or Polymarket using its venue order ID.
输入模式
{'type': 'object', 'title': 'foresea_cancel_orderArguments', 'required': ['order_id'], 'properties': {'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'order_id': {'type': 'string', 'title': 'Order Id'}, 'platform': {'type': 'string', 'title': 'Platform', 'default': 'kalshi'}}}
输出模式
{'type': 'object', 'title': 'foresea_cancel_orderOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_check_run
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.
输入模式
{'type': 'object', 'title': 'foresea_check_runArguments', 'required': ['client_run_key'], 'properties': {'client_run_key': {'type': 'string', 'title': 'Client Run Key'}}}
输出模式
{'type': 'object', 'title': 'foresea_check_runOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_crypto_edge
Scan real-time Kalshi cryptocurrency prediction markets (KXBTCD threshold contracts)
scored against Black-Scholes zero-drift diffusion models and spot volatility. Returns tradeable
market mispricings, implied odds, calibration reliability, and realized paper equity curves.
输入模式
{'type': 'object', 'title': 'foresea_crypto_edgeArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.0}}}
输出模式
{'type': 'object', 'title': 'foresea_crypto_edgeOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_debate_market
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.
输入模式
{'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': None}, 'resolution_criteria': {'type': 'string', 'title': 'Resolution Criteria', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'foresea_debate_marketOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_edge_board
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.
Supports cursor pagination, limit, min_edge threshold, and field masking.
输入模式
{'type': 'object', 'title': 'foresea_edge_boardArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'cursor': {'type': 'integer', 'title': 'Cursor', 'default': 0}, 'fields': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Fields', 'default': None}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.0}}}
输出模式
{'type': 'object', 'title': 'foresea_edge_boardOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_exchange_status
Call this to check Kalshi exchange operational status (trading active flag)
and operational hours/schedule.
输入模式
{'type': 'object', 'title': 'foresea_exchange_statusArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'foresea_exchange_statusOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_feed_latest
Fetch the real-time unified Foresea Alpha & Agent Feed, combining live prediction market edge signals, autonomous agent trades & theses, and leaderboard standings.
输入模式
{'type': 'object', 'title': 'foresea_feed_latestArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 10}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.05}}}
输出模式
{'type': 'object', 'title': 'foresea_feed_latestOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_forecast
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.
输入模式
{'type': 'object', 'title': 'foresea_forecastArguments', 'required': ['question'], 'properties': {'options': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Options', 'default': None}, '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': None}, 'market_url': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Market Url', 'default': None}, 'description': {'type': 'string', 'title': 'Description', 'default': ''}, 'question_type': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Question Type', 'default': None}, 'evidence_top_k': {'type': 'integer', 'title': 'Evidence Top K', 'default': 5}, 'market_outcome': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Market Outcome', 'default': None}, 'attach_evidence': {'type': 'boolean', 'title': 'Attach Evidence', 'default': True}, 'market_platform': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Market Platform', 'default': None}, 'market_probability': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Market Probability', 'default': None}, 'resolution_criteria': {'type': 'string', 'title': 'Resolution Criteria', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'foresea_forecastOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_live_data
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.
输入模式
{'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': ''}}}
输出模式
{'type': 'object', 'title': 'foresea_live_dataOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_market_leaderboard
Call this to fetch the top profitable prediction market trader leaderboard and rankings from Polymarket.
输入模式
{'type': 'object', 'title': 'foresea_market_leaderboardArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}}}
输出模式
{'type': 'object', 'title': 'foresea_market_leaderboardOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
foresea_market_tags
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.
输入模式
{'type': 'object', 'title': 'foresea_market_tagsArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'foresea_market_tagsOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
foresea_optimize_portfolio
Calculate optimal mathematical Fractional Kelly capital allocations and position sizes across live Grade A/B prediction market opportunities.
输入模式
{'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': 1000.0}, 'kelly_fraction': {'type': 'number', 'title': 'Kelly Fraction', 'default': 0.25}}}
输出模式
{'type': 'object', 'title': 'foresea_optimize_portfolioOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_orderbook
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.
输入模式
{'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'}}}
输出模式
{'type': 'object', 'title': 'foresea_orderbookOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_place_order
Submit a guarded real order to Kalshi or Polymarket. Live execution requires
confirmation='PLACE REAL ORDER' and execute=True, and is protected by server
notional ceilings and exchange guardrails.
输入模式
{'type': 'object', 'title': 'foresea_place_orderArguments', 'required': ['platform', 'action', 'outcome', 'price', 'quantity', 'confirmation'], 'properties': {'slug': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Slug', 'default': None}, 'price': {'type': 'number', 'title': 'Price'}, 'action': {'type': 'string', 'title': 'Action'}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'execute': {'type': 'boolean', 'title': 'Execute', 'default': True}, 'outcome': {'type': 'string', 'title': 'Outcome'}, 'platform': {'type': 'string', 'title': 'Platform'}, 'quantity': {'type': 'number', 'title': 'Quantity'}, 'token_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Token Id', 'default': None}, 'post_only': {'type': 'boolean', 'title': 'Post Only', 'default': False}, 'order_type': {'type': 'string', 'title': 'Order Type', 'default': 'limit'}, 'confirmation': {'type': 'string', 'title': 'Confirmation'}, 'time_in_force': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Time In Force', 'default': None}, 'client_order_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Client Order Id', 'default': None}}}
输出模式
{'type': 'object', 'title': 'foresea_place_orderOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_polymarket_meta
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.
输入模式
{'type': 'object', 'title': 'foresea_polymarket_metaArguments', 'properties': {'target': {'type': 'string', 'title': 'Target', 'default': 'series'}, 'market_id': {'type': 'string', 'title': 'Market Id', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'foresea_polymarket_metaOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
foresea_preview_order
Validate, normalize, and simulate guardrail checks for a real Kalshi or
Polymarket order without submitting it to the exchange.
输入模式
{'type': 'object', 'title': 'foresea_preview_orderArguments', 'required': ['platform', 'action', 'outcome', 'price', 'quantity'], 'properties': {'slug': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Slug', 'default': None}, 'price': {'type': 'number', 'title': 'Price'}, 'action': {'type': 'string', 'title': 'Action'}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'outcome': {'type': 'string', 'title': 'Outcome'}, 'platform': {'type': 'string', 'title': 'Platform'}, 'quantity': {'type': 'number', 'title': 'Quantity'}, 'token_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Token Id', 'default': None}, 'post_only': {'type': 'boolean', 'title': 'Post Only', 'default': False}, 'order_type': {'type': 'string', 'title': 'Order Type', 'default': 'limit'}, 'time_in_force': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Time In Force', 'default': None}}}
输出模式
{'type': 'object', 'title': 'foresea_preview_orderOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_price_history
Call this to retrieve historical price series or OHLC candlesticks for a
market (e.g. Kalshi ticker or Polymarket token/slug).
输入模式
{'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'}}}
输出模式
{'type': 'object', 'title': 'foresea_price_historyOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
foresea_recent_trades
Call this to fetch recent public executed trades / trade tape (prices, sizes, timestamps) on Kalshi or Polymarket.
输入模式
{'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': ''}}}
输出模式
{'type': 'object', 'title': 'foresea_recent_tradesOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
foresea_scan_markets
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}].
输入模式
{'type': 'object', 'title': 'foresea_scan_marketsArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 4}, 'query': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Query', 'default': None}, '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}}}
输出模式
{'type': 'object', 'title': 'foresea_scan_marketsOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_track_record
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. Pass optional fields list
(e.g. ['brier_score', 'accuracy', 'n_snapshots_resolved']) to reduce token usage.
输入模式
{'type': 'object', 'title': 'foresea_track_recordArguments', 'properties': {'fields': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Fields', 'default': None}}}
输出模式
{'type': 'object', 'title': 'foresea_track_recordOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_trade_account_status
Check real prediction-market trading readiness, max order notional limits,
and venue configuration statuses for Kalshi and Polymarket.
输入模式
{'type': 'object', 'title': 'foresea_trade_account_statusArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'foresea_trade_account_statusOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_venue_data
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.
输入模式
{'type': 'object', 'title': 'foresea_venue_dataArguments', 'properties': {'body': {'anyOf': [{'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}}, {'type': 'null'}], 'title': 'Body', 'default': None}, 'platform': {'type': 'string', 'title': 'Platform', 'default': ''}, 'operation': {'type': 'string', 'title': 'Operation', 'default': ''}, 'parameters': {'anyOf': [{'type': 'object', 'additionalProperties': True}, {'type': 'null'}], 'title': 'Parameters', 'default': None}}}
输出模式
{'type': 'object', 'title': 'foresea_venue_dataOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_weather_forecast
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.
输入模式
{'type': 'object', 'title': 'foresea_weather_forecastArguments', 'required': ['station_or_query'], 'properties': {'target_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Target Date', 'default': None}, 'station_or_query': {'type': 'string', 'title': 'Station Or Query'}}}
输出模式
{'type': 'object', 'title': 'foresea_weather_forecastOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_weather_radar
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.
输入模式
{'type': 'object', 'title': 'foresea_weather_radarArguments', 'properties': {'target_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Target Date', 'default': None}}}
输出模式
{'type': 'object', 'title': 'foresea_weather_radarOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
foresea_webhook_subscribe
Subscribe an external agent HTTP callback webhook to receive real-time dispatches
for new forecasts and market edge opportunities. The response contains an HMAC secret
(X-Foresea-Signature) for validating incoming payloads.
输入模式
{'type': 'object', 'title': 'foresea_webhook_subscribeArguments', 'required': ['url'], 'properties': {'url': {'type': 'string', 'title': 'Url'}, 'events': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Events', 'default': None}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.05}}}
输出模式
{'type': 'object', 'title': 'foresea_webhook_subscribeOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
历史
近期工具变更
已添加
foresea_cancel_order
2026年10月1日 02:44
已添加
foresea_place_order
2026年10月1日 02:44
已添加
foresea_preview_order
2026年10月1日 02:44
已添加
foresea_trade_account_status
2026年10月1日 02:44
已添加
foresea_webhook_subscribe
2026年10月1日 02:44
已添加
foresea_crypto_edge
2026年10月1日 02:44
已添加
foresea_batch_forecast
2026年10月1日 02:44
已更改
foresea_edge_board
2026年9月29日 02:51
已更改
foresea_track_record
2026年9月29日 02:51
已添加
foresea_weather_forecast
2026年9月17日 12:39
已添加
foresea_weather_radar
2026年9月17日 12:39
已添加
foresea_feed_latest
2026年9月17日 12:39
已添加
foresea_optimize_portfolio
2026年9月17日 12:39
已添加
foresea_debate_market
2026年9月17日 12:39
已添加
foresea_market_leaderboard
2026年9月17日 12:39
已添加
foresea_recent_trades
2026年9月17日 12:39
已添加
foresea_polymarket_meta
2026年9月17日 12:39
已添加
foresea_live_data
2026年9月17日 12:39
已添加
foresea_price_history
2026年9月17日 12:39
已添加
foresea_market_tags
2026年9月17日 12:39
已添加
foresea_orderbook
2026年9月17日 12:39
已添加
foresea_exchange_status
2026年9月17日 12:39
已添加
foresea_venue_data
2026年9月17日 12:39
已添加
foresea_edge_board
2026年9月17日 12:39
已添加
foresea_track_record
2026年9月17日 12:39
已添加
foresea_check_run
2026年9月17日 12:39
已添加
foresea_batch_quotes
2026年9月17日 12:39
已添加
foresea_scan_markets
2026年9月17日 12:39
已添加
foresea_analyze_market
2026年9月17日 12:39
已添加
foresea_forecast
2026年9月17日 12:39
发现
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