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technology-convergence-disruption-mcp

MCP Tool

apifyforge/technology-convergence-disruption-mcp

Technology convergence disruption intelligence — quantified across 14 live data sources and eight statistical models — now available as a Model Context Protocol server your AI agent calls directly.

Install

$ npx loaditout add apifyforge/technology-convergence-disruption-mcp

Platform-specific configuration:

.claude/settings.json
{
  "mcpServers": {
    "technology-convergence-disruption-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "technology-convergence-disruption-mcp"
      ]
    }
  }
}

Add the config above to .claude/settings.json under the mcpServers key.

About

Technology Convergence Disruption MCP Server

> [View on ApifyForge](https://apifyforge.com/actors/mcp-servers/technology-convergence-disruption-mcp) | [Use on Apify Store](https://apify.com/ryanclinton/technology-convergence-disruption-mcp)

---

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf):

{
  "mcpServers": {
    "technology-convergence-disruption-mcp": {
      "url": "https://ryanclinton--technology-convergence-disruption-mcp.apify.actor/mcp"
    }
  }
}

---

Technology convergence disruption intelligence — quantified across 14 live data sources and eight statistical models — now available as a Model Context Protocol server your AI agent calls directly. Connect Claude Desktop, Cursor, or any MCP-compatible client to detect cross-domain patent convergence 3-5 years before it reaches mainstream awareness, trace academic-to-commercial knowledge cascades, and score industries against the Christensen disruption framework from a single endpoint.

This server orchestrates parallel calls to USPTO and EPO patent databases, OpenAlex, Semantic Scholar, arXiv, Crossref, GitHub, Stack Overflow, Hacker News, NIH grants, job market data, EUIPO trademarks, ORCID researcher profiles, and company deep research. Each tool call gathers the appropriate data and feeds results through purpose-built statistical algorithms: bipartite projection cosine similarity for patent convergence, branching process models for knowledge cascades, log-logistic diffusion curve fitting for adoption velocity, Fiedler spectral clustering for skill transitions, and ARDL time-series regression for funding leading indicators.

What data can you access?

| Data Point | Source | Example | |---|---|---| | 📄 Patent filings, IPC/CPC codes, applicants, citations | USPTO Patents | US11,234,567 — G06N 20/00 (AI/ML), filed 2023 | | 🌍 European patent publications and classifications | EPO Patents | EP3891234 — H04L 9/32 (Cryptography), 8 IPC codes | | 📚 Acad

Tags

ai-toolsapifyclaudecursormcpmcp-servermodel-context-protocolwindsurf

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Last updated23 days ago
Security: AREADME

Safety

Risk Levelmedium
Data Access
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Details

Sourcegithub-crawl
Last commit3/21/2026
View on GitHub→

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