Critical Infrastructure Interdependency MCP Server

@apifyforge

About Critical Infrastructure Interdependency MCP Server

Critical infrastructure cascade analysis for AI agents — this MCP server maps cross-sector interdependencies across energy, telecom, water, cyber, transport, and financial networks and simulates how failures propagate through them.

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "critical-infrastructure-interdependency-mcp": {
      "url": "https://ryanclinton--critical-infrastructure-interdependency-mcp.apify.actor/mcp"
    }
  }
}

Tools

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Overview

What is Critical Infrastructure Interdependency MCP Server?

An MCP server that maps cross-sector interdependencies across energy, telecom, water, cyber, transport, and financial networks and simulates how failures propagate through them. It connects AI agents to 8 specialized tools that run 6 mathematical algorithms on real data from 14 live sources.

How to use Critical Infrastructure Interdependency MCP Server?

Add the MCP endpoint URL to your client’s configuration (Claude Desktop, Cursor, or Windsurf) using the provided JSON block. No API key is needed in the config – the server handles authentication. Then ask your agent to call build_infrastructure_network with a region name, followed by analysis tools such as simulate_cascade_failure or identify_critical_nodes.

Key features of Critical Infrastructure Interdependency MCP Server

6-layer multiplex hypergraph construction from real infrastructure data
BTW sand-pile cascade simulation for self-organized criticality
Voronoi geographic co-location risk with hazard overlay
CPM recovery timeline estimation with sector restoration order
Supra-Laplacian algebraic connectivity indexing for resilience classification
Multi-metric critical node identification (cascade impact, connectivity, centrality)

Use cases of Critical Infrastructure Interdependency MCP Server

Emergency management and disaster preparedness for simulating natural disaster impacts
Critical infrastructure protection and investment prioritization via node ranking
Cyber-physical threat modeling for ICS/OT security teams
Infrastructure resilience auditing and regulatory compliance (NERC CIP, TSA, DORA)
Insurance underwriting and catastrophe risk modeling for co-location hazards

FAQ from Critical Infrastructure Interdependency MCP Server

What data sources does the server use?

The server pulls from 14 live sources including OpenStreetMap, DNS records, Censys, crt.sh, NVD, CISA KEV, USGS earthquakes, NOAA weather alerts, FEMA disasters, UK flood monitoring, GDACS, and Nominatim.

What tools are available?

Eight tools: build_infrastructure_network, simulate_cascade_failure, compute_geographic_correlation, identify_critical_nodes, model_natural_disaster_impact, assess_cyber_physical_attack, generate_resilience_assessment, and estimate_recovery_timeline.

Is any setup or API key required in the client?

No. The client configuration only needs the MCP endpoint URL. The server handles authentication and runs on the Apify platform – no client-side API key is necessary.

How fast are tool calls?

Parallel actor orchestration reduces total wall time from 20+ minutes to 3–5 minutes per tool call by running up to 14 underlying data actors concurrently.

Are there spending limits?

Every tool call checks the Actor.charge() event limit before running. If the per-run budget is reached, the tool halts cleanly.

Frequently asked questions

What data sources does the server use?

What tools are available?

Eight tools: `build_infrastructure_network`, `simulate_cascade_failure`, `compute_geographic_correlation`, `identify_critical_nodes`, `model_natural_disaster_impact`, `assess_cyber_physical_attack`, `generate_resilience_assessment`, and `estimate_recovery_timeline`.

Is any setup or API key required in the client?

No. The client configuration only needs the MCP endpoint URL. The server handles authentication and runs on the Apify platform – no client-side API key is necessary.

How fast are tool calls?

Parallel actor orchestration reduces total wall time from 20+ minutes to 3–5 minutes per tool call by running up to 14 underlying data actors concurrently.

Are there spending limits?

Every tool call checks the `Actor.charge()` event limit before running. If the per-run budget is reached, the tool halts cleanly.

Comments

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