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Futuristic Risk Intelligence

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Geopolitical conflict risk data for AI agents

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Описание

Geopolitical conflict risk data for AI agents

README

Geopolitical conflict risk data for AI agents via Model Context Protocol (MCP). Updated daily.

PyPI war-dashboard-data MCP server

MCP Tools

Tool Description
get_conflict_risks Risk probabilities for 6 major geopolitical conflicts (escalation, ceasefire, regime change) with 1d/7d/30d horizons
get_political_events High-impact political, economic, and natural disaster events with probability estimates
get_maritime_traffic ⚠️ Suspended — AIS snapshot data does not meet reliability standards. Returns status: unavailable.

Install

pip install war-dashboard-data

Quick Start

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "futuristic-risk": {
      "command": "war-dashboard-data"
    }
  }
}

Then ask Claude: "What's the current escalation risk for Russia-Ukraine?"

Direct API (REST)

curl https://raw.githubusercontent.com/cct15/war-dashboard-data/main/conflicts.json

Coverage

6 conflict regions: Russia-Ukraine, Iran-Israel/US, Israel-Palestine, China-Taiwan, India-Pakistan, US-Latin America

5 event types with clear risk direction:

Event Type Meaning Direction
escalation Military escalation (strikes, invasion, nuclear test) risk_increase
ceasefire Ceasefire or peace agreement reached risk_decrease
ceasefire_cancel Existing ceasefire breaks down risk_increase
regime_change Government falls or changes risk_increase
diplomatic Major diplomatic event (nuclear deal, treaty) neutral

Data Schema

conflicts.json

Each conflict includes:

Field Description
conflict_id Region identifier (e.g. russia_ukraine, iran_israel_us)
importance Editorial priority: high (active/major conflict, recommended for display) or low (low probability, included for data completeness)
risk_level Overall risk: high / medium / low
probability_30d / 7d / 1d P(event occurs within time horizon)
situation_briefing Daily situation summary in Chinese, based on latest news
risk_impact Structured impact analysis: industries[], assets[], channels[] (transmission paths)
risk_events[] Breakdown by event type with per-type probabilities
risk_events[].direction risk_increase (higher prob = more danger) or risk_decrease (higher prob = less danger)
risk_events[].change_vs_7d_ago Probability delta vs. 7 days ago
data_points Number of data sources (for confidence assessment)
anomaly_detected Whether probability diverges from news intensity

political_events.json

Political, economic, and natural disaster events with probability estimates.

Field Description
event_summary Event description (Chinese)
event_summary_en Event description (English)
category political / economic / natural_disaster
probability Estimated probability of occurrence
importance Editorial priority: high (recommended for display) or low (data completeness)
deadline Event deadline (YYYY-MM-DD), if applicable
data_confidence high / medium / low (based on trading volume)

importance field

Both conflicts.json and political_events.json include an importance field:

  • high — Editorially recommended. Active conflicts, high-probability events, or events with significant recent changes. Matches the daily intelligence report's display filter.
  • low — Included for data completeness. Low probability, no active events, or not a current focus area. Agents may still find these useful for comprehensive monitoring.

maritime.json

⚠️ Suspended: Free AIS data (45-second snapshots) produces sporadic zero-vessel readings in busy straits, which could mislead agents into inferring blockades. Returns {"status": "unavailable", "zones": []}. Will resume when a reliable AIS source is found.

Use Cases

  • Trading agents: Adjust crypto/commodity positions based on geopolitical risk changes
  • Risk management: Monitor conflict escalation probabilities for portfolio hedging
  • DeFi protocols: Dynamic collateral ratios based on geopolitical risk
  • Research agents: Track probability trends across 6 conflict regions
  • News agents: Get structured risk data instead of parsing headlines

Technical Details

  • Zero dependencies: MCP server uses only Python stdlib (works with Python 3.9+)
  • Data source: Proprietary multi-source modeling
  • Update frequency: Daily
  • Latency: Public data has ~24h delay

License

Data is free for non-commercial use. Contact for commercial licensing.

Website & Research

futuristicrisks.com — Live risk dashboard, cascade impact analysis, daily verified intelligence, and API documentation.

Research articles:

Built by Futuristic Risk Intelligence.

from github.com/cct15/war-dashboard-data

Установить Futuristic Risk Intelligence в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install futuristic-risk-intelligence

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add futuristic-risk-intelligence -- uvx war-dashboard-data

Пошаговые гайды: как установить Futuristic Risk Intelligence

FAQ

Futuristic Risk Intelligence MCP бесплатный?

Да, Futuristic Risk Intelligence MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Futuristic Risk Intelligence?

Нет, Futuristic Risk Intelligence работает без API-ключей и переменных окружения.

Futuristic Risk Intelligence — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить Futuristic Risk Intelligence в Claude Desktop, Claude Code или Cursor?

Открой Futuristic Risk Intelligence на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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