Foresea Forecasting
Forecast future events and scan prediction-market edges.
| Endpoint | https://foresea.ink/mcp/ (streamable-http) |
|---|---|
| Registry version | 1.0.0 |
| Now | 28 tools · grade C (74) · pin ts_54c5515e459829d078fd25cfccba8cf4 · protocol 2025-06-18 |
| First / last listed | 2026-11-02 03:29 UTC / 2026-11-02 03:29 UTC |
| Grade over time | 2026-11-02: C (74), 28 tools |
Is this your server? Own a server? ToolFit hosted watch re-checks it every 24 h ($0.25 per 30 days) or 6 h ($0.60) and sends you an HMAC-signed webhook when its tools or grade change: POST https://api.youraitools.co/toolfit/v1/watch. To opt out, see About & opt-out.
Tools: foresea_forecast foresea_analyze_market foresea_scan_markets foresea_batch_quotes foresea_check_run foresea_track_record foresea_edge_board foresea_venue_data foresea_exchange_status foresea_orderbook foresea_market_tags foresea_price_history foresea_live_data foresea_polymarket_meta foresea_recent_trades foresea_market_leaderboard foresea_debate_market foresea_optimize_portfolio foresea_feed_latest foresea_weather_radar foresea_weather_forecast foresea_batch_forecast foresea_crypto_edge foresea_webhook_subscribe foresea_trade_account_status foresea_preview_order foresea_place_order foresea_cancel_order
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 evid params: question*, description, resolution_criteria, question_type, options, categories, variant, attach_evidence, evidence_top_k, market_platform, market_url, market_outcome, market_probability |
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 params: question, platform, slug, market_id, ticker, market_probability, variant, evidence_top_k, skills, builtin_skills, ground_in_record, tool_loop, max_tool_steps |
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
params: platform, limit, min_edge, evidence_top_k, query |
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 freshne params: refs* |
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 params: client_run_key* |
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 params: fields |
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 params: limit, min_edge, fields, cursor |
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. params: platform, operation, parameters, body |
foresea_exchange_status | Call this to check Kalshi exchange operational status (trading active flag)
and operational hours/schedule. params: none |
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. params: ticker_or_token*, platform |
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, presen params: none |
foresea_price_history | Call this to retrieve historical price series or OHLC candlesticks for a
market (e.g. Kalshi ticker or Polymarket token/slug). params: ticker_or_market*, series_ticker |
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. params: event_ticker, data_type, milestone_id |
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 params: target, market_id |
foresea_recent_trades | Call this to fetch recent public executed trades / trade tape (prices, sizes, timestamps) on Kalshi or Polymarket. params: platform, ticker_or_token, limit |
foresea_market_leaderboard | Call this to fetch the top profitable prediction market trader leaderboard and rankings from Polymarket. params: limit |
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. params: question*, platform, market_probability, resolution_criteria |
foresea_optimize_portfolio | Calculate optimal mathematical Fractional Kelly capital allocations and position sizes across live Grade A/B prediction market opportunities. params: bankroll_usd, kelly_fraction, min_edge |
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. params: limit, min_edge |
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-v params: target_date |
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. params: station_or_query*, target_date |
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. params: questions, items, concurrency_limit, variant, attach_evidence, evidence_top_k |
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. params: min_edge, limit |
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. params: url*, events, min_edge |
foresea_trade_account_status | Check real prediction-market trading readiness, max order notional limits,
and venue configuration statuses for Kalshi and Polymarket. params: none |
foresea_preview_order | Validate, normalize, and simulate guardrail checks for a real Kalshi or
Polymarket order without submitting it to the exchange. params: platform*, action*, outcome*, price*, quantity*, order_type, ticker, slug, token_id, time_in_force, post_only |
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. params: platform*, action*, outcome*, price*, quantity*, confirmation*, execute, order_type, ticker, slug, token_id, time_in_force, post_only, client_order_id |
foresea_cancel_order | Cancel an active open order on Kalshi or Polymarket using its venue order ID. params: order_id*, platform, ticker |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.