MCP-Server
Foresea Forecasting
ink.foresea/forecasting
Was dieses MCP kann
Forecasts events, analyzes prediction markets, scans for market edges, and provides market data, weather forecasts, and portfolio allocation analysis.
Funktionen
Tools
28
Tools
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}.
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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}.
Eingabeschema
{'type': 'object', 'title': 'foresea_batch_quotesArguments', 'required': ['refs'], 'properties': {'refs': {'type': 'array', 'items': {'type': 'string'}, 'title': 'Refs'}}}
Ausgabeschema
{'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.
Eingabeschema
{'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'}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_check_runArguments', 'required': ['client_run_key'], 'properties': {'client_run_key': {'type': 'string', 'title': 'Client Run Key'}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_crypto_edgeArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.0}}}
Ausgabeschema
{'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.
Eingabeschema
{'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': ''}}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_exchange_statusArguments', 'properties': {}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_feed_latestArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 10}, 'min_edge': {'type': 'number', 'title': 'Min Edge', 'default': 0.05}}}
Ausgabeschema
{'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.
Eingabeschema
{'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': ''}}}
Ausgabeschema
{'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.
Eingabeschema
{'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': ''}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_market_leaderboardArguments', 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_market_tagsArguments', 'properties': {}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'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'}}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_polymarket_metaArguments', 'properties': {'target': {'type': 'string', 'title': 'Target', 'default': 'series'}, 'market_id': {'type': 'string', 'title': 'Market Id', 'default': ''}}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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).
Eingabeschema
{'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'}}}
Ausgabeschema
{'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.
Eingabeschema
{'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': ''}}}
Ausgabeschema
{'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}].
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_track_recordArguments', 'properties': {'fields': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Fields', 'default': None}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_trade_account_statusArguments', 'properties': {}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'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.
Eingabeschema
{'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'}}}
Ausgabeschema
{'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.
Eingabeschema
{'type': 'object', 'title': 'foresea_weather_radarArguments', 'properties': {'target_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Target Date', 'default': None}}}
Ausgabeschema
{'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.
Eingabeschema
{'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}}}
Ausgabeschema
{'type': 'object', 'title': 'foresea_webhook_subscribeOutput', 'required': ['result'], 'properties': {'result': {'type': 'object', 'title': 'Result', 'additionalProperties': True}}}
Verlauf
Letzte Tool-Änderungen
Hinzugefügt
foresea_cancel_order
1. October 2026 02:44
Hinzugefügt
foresea_place_order
1. October 2026 02:44
Hinzugefügt
foresea_preview_order
1. October 2026 02:44
Hinzugefügt
foresea_trade_account_status
1. October 2026 02:44
Hinzugefügt
foresea_webhook_subscribe
1. October 2026 02:44
Hinzugefügt
foresea_crypto_edge
1. October 2026 02:44
Hinzugefügt
foresea_batch_forecast
1. October 2026 02:44
Geändert
foresea_edge_board
29. September 2026 02:51
Geändert
foresea_track_record
29. September 2026 02:51
Hinzugefügt
foresea_weather_forecast
17. September 2026 12:39
Hinzugefügt
foresea_weather_radar
17. September 2026 12:39
Hinzugefügt
foresea_feed_latest
17. September 2026 12:39
Hinzugefügt
foresea_optimize_portfolio
17. September 2026 12:39
Hinzugefügt
foresea_debate_market
17. September 2026 12:39
Hinzugefügt
foresea_market_leaderboard
17. September 2026 12:39
Hinzugefügt
foresea_recent_trades
17. September 2026 12:39
Hinzugefügt
foresea_polymarket_meta
17. September 2026 12:39
Hinzugefügt
foresea_live_data
17. September 2026 12:39
Hinzugefügt
foresea_price_history
17. September 2026 12:39
Hinzugefügt
foresea_market_tags
17. September 2026 12:39
Hinzugefügt
foresea_orderbook
17. September 2026 12:39
Hinzugefügt
foresea_exchange_status
17. September 2026 12:39
Hinzugefügt
foresea_venue_data
17. September 2026 12:39
Hinzugefügt
foresea_edge_board
17. September 2026 12:39
Hinzugefügt
foresea_track_record
17. September 2026 12:39
Hinzugefügt
foresea_check_run
17. September 2026 12:39
Hinzugefügt
foresea_batch_quotes
17. September 2026 12:39
Hinzugefügt
foresea_scan_markets
17. September 2026 12:39
Hinzugefügt
foresea_analyze_market
17. September 2026 12:39
Hinzugefügt
foresea_forecast
17. September 2026 12:39
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