Cognitive Warfare & PsyOps Analysis

What is Cognitive Warfare & PsyOps Analysis?

An MCP server that provides AI agents with eight specialized tools for cognitive warfare and psychological operations analysis. It accesses 16 parallel Apify data sources—social media, regulatory, sanctions, infrastructure, geopolitical, and archival—and applies quantitative frameworks from epidemiology, evolutionary biology, statistical physics, and game theory. Built for STRATCOM analysts, platform integrity teams, counter-disinformation researchers, and intelligence-augmented AI agents.

How to use Cognitive Warfare & PsyOps Analysis?

Add the server to your MCP client (Claude Desktop, Cursor, Windsurf) using the provided JSON configuration. The server exposes eight tools callable from any MCP-compatible client, each returning structured JSON. Tools are priced per call and check spending limits before execution.

Key features of Cognitive Warfare & PsyOps Analysis

• 8 tools covering detection, modeling, optimization, and forecasting
• Coupled SIR-Hawkes model for coordinated operation classification
• Bayesian Stackelberg game for counter-narrative timing optimization
• Persistent homology to measure echo chambers and fragmentation
• Doubly-robust causal inference for attribution of narrative effects
• Price equation evolutionary dynamics for memetic competition
• Haar wavelet packet decomposition for cross-scale coordination
• Seeded PRNG for reproducible scoring across runs

Use cases of Cognitive Warfare & PsyOps Analysis

• Government STRATCOM early warning of coordinated narrative operations
• Counter-disinformation strategy via Stackelberg equilibrium intervention timing
• Social media platform integrity detection of inauthentic coordinated behavior
• Academic research on belief dynamics and memetic evolution
• Crisis communication vulnerability assessment using polarization phase transitions
• Attribution and causal forensics for narrative source identification

FAQ from Cognitive Warfare & PsyOps Analysis

How does this server differ from traditional social listening tools?

Traditional tools count mentions and measure sentiment. This server provides quantitative frameworks—SIR epidemic modeling, Bayesian game theory, topological data analysis—to detect coordination, attribute causality, forecast polarization transitions, and optimize intervention timing.

What data sources does it access?

16 sources in parallel: Bluesky Social, Hacker News, Wikipedia, Federal Register, Interpol Red Notices, OpenSanctions, Website Change Monitor, Wayback Machine, REST Countries, GDACS Disaster Alerts, Congress Bill Tracker, NOAA Weather, GitHub Repo Search, Website Content to Markdown, DNS Lookup, and IP Geolocation.

Does the server require any infrastructure or data pipelines?

No. The server runs as an Apify actor. No infrastructure to manage or data pipeline to build. Query 16 sources in parallel via a single tool call.

Are there runtime or cost limits?

Each tool call has a fixed price (e.g., $0.050 for detect_narrative_operations). The server checks your event charge limit before executing and stops gracefully if reached. The server stays warm between calls via standby mode, eliminating cold start latency.

What mathematical frameworks are applied?

Coupled SIR-Hawkes, DeGroot social learning, Bayesian Stackelberg games, submodular greedy influence maximization, persistent homology, doubly-robust causal inference, Price equation evolutionary dynamics, Haar wavelet packet decomposition, and q-state Potts model for phase transition forecasting.