Futuristic Risk Intelligence

io.github.cct15Published by GitHub account cct15v1.0.0Updated Oct 25, 2026

Geopolitical conflict risk, political events, and maritime traffic data for AI agents

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Overview

AI-generated overview

A local MCP server that gives an assistant daily geopolitical conflict risk probabilities, political event forecasts, and a suspended maritime traffic feed.

What you can do
Retrieve conflict risk probabilities for six regions across 1-day, 7-day and 30-day horizons, with risk levels, event-type breakdowns and change versus a week ago. Read high-impact political, economic and natural disaster events with probability estimates, deadlines and confidence ratings. Review structured impact analysis per conflict, including affected industries, assets and transmission channels. Query maritime traffic data, which currently returns an unavailable status.
When to use it
Useful for research, news or risk-monitoring assistants that want structured geopolitical risk numbers instead of parsing headlines, for example tracking escalation trends across regions or feeding risk context into portfolio and supply-chain analysis.
Requirements
Runs as a local process installed from PyPI (war-dashboard-data) with Python 3.9 or later; no dependencies beyond the standard library. No authentication, API keys or environment variables are declared. Data is bundled and updated daily, with roughly a 24-hour delay.
Before you install
Probabilities are model estimates from a proprietary source, not verified facts, and should not be treated as advice for trading or hedging decisions. The maritime tool is suspended and returns no data. Situation briefings are partly in Chinese. Data is about a day old.

Installation

In SourceWeft

  1. Open Futuristic Risk Intelligence in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Futuristic Risk Intelligence — MCP Server & Data Feed

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

[PyPI] [war-dashboard-data MCP server]

MCP Tools

ToolDescription
get_conflict_risksRisk probabilities for 6 major geopolitical conflicts (escalation, ceasefire, regime change) with 1d/7d/30d horizons
get_political_eventsHigh-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

bash
pip install war-dashboard-data

Quick Start

Claude Desktop

Add to your claude_desktop_config.json:

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

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

Direct API (REST)

bash
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 TypeMeaningDirection
escalationMilitary escalation (strikes, invasion, nuclear test)risk_increase
ceasefireCeasefire or peace agreement reachedrisk_decrease
ceasefire_cancelExisting ceasefire breaks downrisk_increase
regime_changeGovernment falls or changesrisk_increase
diplomaticMajor diplomatic event (nuclear deal, treaty)neutral

Data Schema

conflicts.json

Each conflict includes:

FieldDescription
conflict_idRegion identifier (e.g. russia_ukraine, iran_israel_us)
importanceEditorial priority: high (active/major conflict, recommended for display) or low (low probability, included for data completeness)
risk_levelOverall risk: high / medium / low
probability_30d / 7d / 1dP(event occurs within time horizon)
situation_briefingDaily situation summary in Chinese, based on latest news
risk_impactStructured impact analysis: industries[], assets[], channels[] (transmission paths)
risk_events[]Breakdown by event type with per-type probabilities
risk_events[].directionrisk_increase (higher prob = more danger) or risk_decrease (higher prob = less danger)
risk_events[].change_vs_7d_agoProbability delta vs. 7 days ago
data_pointsNumber of data sources (for confidence assessment)
anomaly_detectedWhether probability diverges from news intensity

political_events.json

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

FieldDescription
event_summaryEvent description (Chinese)
event_summary_enEvent description (English)
categorypolitical / economic / natural_disaster
probabilityEstimated probability of occurrence
importanceEditorial priority: high (recommended for display) or low (data completeness)
deadlineEvent deadline (YYYY-MM-DD), if applicable
data_confidencehigh / 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.

Source: README.md at commit c7f27ba

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts