Technology Convergence Disruption MCP Server
@apifyforge
关于 Technology Convergence Disruption MCP Server
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.
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"technology-convergence-disruption-mcp": {
"url": "https://ryanclinton--technology-convergence-disruption-mcp.apify.actor/mcp"
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Technology Convergence Disruption MCP Server?
A Model Context Protocol server that delivers technology convergence disruption intelligence by connecting AI agents to 14 live data sources and eight statistical models. It enables detection of cross-domain patent convergence 3–5 years early, traces academic-to-commercial knowledge cascades, and scores industries against the Christensen disruption framework from a single endpoint.
How to use Technology Convergence Disruption MCP Server?
Add the server configuration to your MCP client (e.g., Claude Desktop, Cursor, Windsurf) with the provided URL and your Apify API token. Then instruct your AI assistant to run any of the eight tools, such as “Detect technology convergence in quantum computing with 3-year temporal windows.”
Key features of Technology Convergence Disruption MCP Server
- Bipartite patent convergence analysis across IPC sections
- Branching process cascade model for knowledge flow
- Log-logistic diffusion curve fitting for adoption velocity
- Fiedler spectral clustering for skill transitions
- Christensen disruption scoring with five decomposed factors
- ARDL funding leading indicator from grants to patents
- Parallel data collection from 14 sources per request
- Spend limit enforcement preventing budget overrun
Use cases of Technology Convergence Disruption MCP Server
- Corporate strategy teams identify technology convergence 3–5 years early using patent cosine similarity.
- Venture capital analysts distinguish genuine disruption from momentum with Christensen disruption scores.
- R&D directors allocate budgets based on funding-to-commercialization conversion lags.
- Workforce planners forecast emerging skill clusters via spectral job posting analysis.
- Academic tech transfer offices prioritize licensing opportunities from near-supercritical research topics.
- Established companies quantify threat from adjacent converging technologies.
FAQ from Technology Convergence Disruption MCP Server
How do I connect the server?
Get your Apify API token from Console > Settings > Integrations, then add the server configuration to your MCP client. The server URL is provided in the Quick Start section.
What data sources does it access?
It accesses 14 sources: USPTO Patents, EPO Patents, OpenAlex, Semantic Scholar, arXiv, Crossref, GitHub, Stack Overflow, Hacker News, Job Market Intel, Company Deep Research, NIH Research Grants, EUIPO Trademarks, and ORCID.
How much does each tool call cost?
Each tool has a fixed event price: detect_technology_convergence $0.08, trace_knowledge_cascade $0.07, measure_adoption_velocity $0.06, map_skill_transitions $0.07, score_disruption_risk $0.09, predict_from_research_funding $0.08, profile_technology_landscape $0.08, and full_disruption_brief (price not given but listed as a feature).
Can I schedule recurring analyses?
Yes. The server supports scheduling for weekly patent convergence scans or monthly landscape reports to track technology trajectories over time.
What statistical models are applied?
Eight models: bipartite cosine similarity for patent convergence, branching process for knowledge cascades, log-logistic diffusion for adoption velocity, Fiedler spectral clustering for skill transitions, Christensen scoring for disruption risk, ARDL time-series for funding leads, technology landscape profiler, and full disruption brief synthesis.
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