Futuristic Risk Intelligence — MCP Server & Data Feed

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

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

... View full README on GitHub