What data sources does it use?
It orchestrates 16 Apify actors: USPTO, EPO, OpenAlex, Semantic Scholar, arXiv, DBLP, CORE, GitHub, Stack Overflow, Hacker News, Finnhub, CoinGecko, NIH Grants, Grants.gov, ClinicalTrials.gov, and Data.gov.
@apifyforge
基本情報
Technology convergence prediction is the primary use case for this MCP server — it analyses when and how separate technology domains will merge into unified frameworks, using data from 16 simultaneous sources.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"omega-point-convergence-mcp": {
"url": "https://ryanclinton--omega-point-convergence-mcp.apify.actor/mcp"
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
このサーバーは認証が必要です。ツールの取得にはログインや提供元の認証情報が必要な場合があります。
上のボタンでサーバーのエンドポイントに接続し、ツール一覧を取得できます。
An MCP server that predicts when and how separate technology domains will converge, using data from 16 simultaneous sources and eight independent mathematical algorithms. It is designed for technology strategists, R&D leaders, and venture investors who need quantitative convergence probability, timeline, and phase classification.
Add the server URL to your MCP client (Claude Desktop, Cursor, Windsurf) using the endpoint https://ryanclinton--omega-point-convergence-mcp.apify.actor/mcp. No API key is needed in the connection URL. Then call tools like forecast_omega_point_timing with a technology name and optional depth ("standard" or "deep").
It orchestrates 16 Apify actors: USPTO, EPO, OpenAlex, Semantic Scholar, arXiv, DBLP, CORE, GitHub, Stack Overflow, Hacker News, Finnhub, CoinGecko, NIH Grants, Grants.gov, ClinicalTrials.gov, and Data.gov.
The server runs eight algorithms independently, then synthesises results using a composite score weighting topological complexity, S-curve phase, and stratified gradient to produce a single probability with a ±0.15 confidence interval.
No API key is required in the connection URL; the Apify token is handled server-side by the platform.
Charging is per-tool pay-per-event with a configured spending limit; runs terminate cleanly when the budget is reached rather than producing partial results.
The `forecast_omega_point_timing` tool accepts `depth: "standard"` (75 results per source, faster and cheaper) or `depth: "deep"` (150 results per source, more data).

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