@apifyforge
基本信息
Cognitive warfare and PSYOPS analysis for AI agents via the Model Context Protocol.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"cognitive-warfare-psyops-mcp": {
"url": "https://ryanclinton--cognitive-warfare-psyops-mcp.apify.actor/mcp"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,直接连接服务器端点实时获取工具列表。
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.
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.
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.
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.
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.
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.
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.
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