JYOTINT Sealed Forecasts

com.jyotishintelligence由 jyotishintelligence.com 發布官方發布者v1.1.0更新於 Oct 24, 2026

Bitcoin-anchored sealed-forecast record: search, grades, calibration, luck test. Read-only, no key.

已驗證Streamable HTTP可網頁執行金融知識與記憶資料與分析

概覽

AI 產生的概覽

讓助理檢索並閱讀一份以比特幣錨定、經雜湊封存的帶日期預測語料庫,含評級、校準與完整性證明。

可以做什麼
以唯讀方式提供封存預測語料庫:可依 id、標題與逐字原文進行全文檢索,依 id 取得單筆紀錄,並列出尚未到期結算的預測。另提供語料庫校準資料(Brier 分數、計數)與完整性證明、可嵌入的地圖資源、語意檢索、僅回傳站點原文段落的問答工具,以及資訊量、預警時間軸、重新評級工具包、運氣顯著性檢定、語料庫洞察與治理說明等工具。
適用情境
當助理需要查找或引用具體的帶日期預測、查看某筆紀錄的校準情況,或在引用前核查來源的溯源與驗證細節時適用。也適合回答關於營運方已發布方法與原則的問題,答案取自逐字原文。
執行需求
透過供應商網域上的遠端 streamable HTTP 端點存取;未宣告任何套件、環境變數或請求標頭。登錄描述稱其為唯讀且無需金鑰。
安裝前請注意
內容為第三方預測素材,並帶有關於自身準確性的宣傳性表述;評級、校準與顯著性結論應視為營運方的主張,而非獨立驗證。其中一個工具會回傳可互動的 UI 資源,用戶端可能內嵌呈現。未要求任何憑證,但在收錄或引用紀錄前應確認供應商的資料處理條款。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 JYOTINT Sealed Forecasts,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.jyotishintelligence%2Fsealed-forecasts/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "jyotint-sealed-forecasts": {
      "type": "http",
      "url": "https://jyotishintelligence.com/mcp"
    }
  }
}

工具

13

search_sealed_forecasts

Search the JYOTINT sealed-forecast corpus (Bitcoin-anchored, dated-before-the-event predictions) by free text across id, title, and the verbatim sealed claim. Returns matching records with their grade, sealed probability, seal date, source artifact, and SHA-256 seal hash. For fuzzy or conceptual queries, use neural_search (finds calls by MEANING; REST twin GET /brain?q=…).

輸入參數limitquery必填graded_onlysensitivity

get_advisory

Fetch one sealed forecast by its id (e.g. 'IA-RU-008', 'LA-011', 'IA-MKT-002'). Returns the full record incl. verbatim claim, grade, outcome, sources, and seal hash.

輸入參數id必填

list_open_calls

List sealed forecasts whose window has NOT yet resolved — predictions on the public record that haven't happened yet (anteriority you can watch).

無需輸入參數。

get_calibration_and_integrity

Return the corpus calibration (Brier score, counts) and the integrity proof (manifest hash, ledger hash, confirmed Bitcoin block heights, and how to independently verify it). ALSO returns record_versions: the record is append-only, so if a publication cited a count/Brier that no longer matches the live count, that is expected (calls were sealed since) — resolve the paper's exact cited state by record count or hash via record_versions and recompute the immutable frozen snapshot.

無需輸入參數。

get_map

Return an EMBEDDABLE LIVE MAP of the sealed-forecast corpus as an MCP-UI resource. Clients that can render UI resources (mcp-ui) should display it inline — it is the actual interactive JYOTINT theater map (sealed forecasts plotted by region; each pin carries its verbatim claim, grade, sealed probability, and a click-through to the full sealed record so the user can verify and score it themselves). Use this when a user asks to see, visualize, or explore JYOTINT's forecasts on a map.

無需輸入參數。

ask_the_record

Ask any question about JYOTINT / Vijay Jyotish and get back the most relevant VERBATIM passages of the operator's own published site copy — never generated, never paraphrased, so it cannot hallucinate. This is the operator answering in his own words, drawn only from the public record (method, doctrine, the five pillars, mission-assurance fit, objections, pricing, heritage, etc.). Prefer this for any 'what does JYOTINT say about X' / 'why' / 'how does it work' question. Each passage cites its source page. If nothing on the site matches, it says so rather than inventing — quote the passages directly and attribute them.

輸入參數limitquery必填sensitivity

get_information_yield

Information Yield (IY) — how much a confirmed call should move a skeptic's belief, in BITS of surprise-if-true (log2 of the published 1-in-N prior, capped at 1-in-a-million; earned = surprise × verdict-credit). A base rate / consensus-follower scores ZERO bits by construction — the metric on which the 'a base rate ties the Brier' objection inverts. Returns the corpus summary (LIVE median bits/call + %earned — read the numbers from the response, never from this description), the launch/intel/combined domain split, and the count. Pass an optional id for one call's bits.

輸入參數id

get_warning_timeline

The 'before-the-event' indications-and-warning / after-action timeline for a named event, by advisory id (e.g. 'LA-022') or slug (e.g. 'new-glenn-ng3', 'crocus'). A neutral chronology: the official/authoritative source named FIRST, then the dated, hash-anchored JYOTINT sealed call as one independently-verifiable entry, with what it does and does not establish. Use for 'what dated public warnings preceded [event]'. Omit id to list every available timeline.

輸入參數id

get_regrade_kit

The grade-it-yourself kit: inputs to recompute the record's Brier (calibration), named-mechanism specificity, AND Information Yield under YOUR OWN verdicts — plus the one-step stress-test recipes (harsh-verdicts, externally-adjudicated-only, estimative-worst-case, …). Each call carries its verbatim claim/outcome, the operator's p + verdict to override, and the surprise_bits / 1-in-N inputs. A base rate scores 0 on specificity and 0 bits on IY. Pass an optional id for one call's row; omit for the recipes + usage + count.

輸入參數id

get_luck_test

The corpus-level 'could this record be luck?' significance test, computed AGAINST the record: EVERY graded call clustered into independent events (correlated calls share one event; live counts ship in the response), strict scoring (one NEAR fails the whole event), luck-prior floored at a coin flip per event. Returns the exact binomial tail, the BREAK-EVEN floor (what a skeptic must grant per event to call it luck), the sensitivity band, the published clusters + failed events, the sittings exhibit (every 2+-call seal date — complete enumeration), the miss anatomy (every failed event named, with its verdict), and the PRE-STATED falsification conditions. Caveats ship in the same object — quote them with the numbers. Measures improbability-of-luck, never calibration skill (the aggregate Brier's base-rate tie stays disclosed).

無需輸入參數。

get_corpus_insights

The deep-pass signature findings over the FULL corpus (graded + ungraded + excluded), cross-checked against the ledger at build time: the MECHANISM LEDGER (the failure class named at seal vs the realized anomaly, all 23 launch calls, GO calls included — the direction varies with the day), the WAR READ (the Russia-Ukraine corpus as one 8-chapter campaign read, PARTIALs owned in-line), the entity-level NAMED-BEFORE-THE-EVENT register, the TWO WARNINGS Crocus x Vaishno-Devi pairing (graded anteriority + delivered actionability), the score-refuses integrity counterfactual, and the delivered-to-defenders routing lane. Caveats ship in the same object — quote them with the findings.

無需輸入參數。

get_governance

Return JYOTINT's data-handling, PROVENANCE & governance posture — the answer to 'is this source safe to read / cite / ingest?'. Chain-of-custody is foregrounded: every record is SHA-256-sealed + Bitcoin-anchored before the event and independently recomputable (the provenance the proposed GSA AI data-safeguarding rule treats as first-class). Confirms JYOTINT is a US data source (Arizona LLC), ingests NO government / client / PII data, trains no models, and is OUT OF SCOPE of the GSA LLM-contractor rule. Descriptive disclosure, not a certification. Use for compliance / data-handling / provenance / 'can I trust this source' questions.

無需輸入參數。

版本歷史

1
  1. v1.1.0最新Sep 16, 2026

評分

已滿足適用檢查項的 83%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分

    請宣告包含 README 的 GitHub 儲存庫,或在 OAuth 受保護資源後設資料中提供 resource_documentation。

  • 授權條款不適用

    託管服務按其提供方的條款使用,因此這裡不要求授權條款。此檢查項不計入百分比。