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Sovereign Debt Crisis MCP Server

@apifyforge

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基本情報

カテゴリ

その他

ライセンス

MIT

認証方式

oauth

作者

apifyforge

Sovereign Debt Crisis MCP Server について

Sovereign debt crisis modeling for AI agents and LLM workflows — this MCP server delivers eight academically-grounded simulation tools spanning default dynamics, contagion networks, fiscal sustainability, restructuring design, speculative attacks, and political regime transitions

Sovereign Debt Crisis MCP Server の設定

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": {
    "sovereign-debt-crisis-mcp": {
      "url": "https://ryanclinton--sovereign-debt-crisis-mcp.apify.actor/mcp"
    }
  }
}

Sovereign Debt Crisis MCP Server のツール

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。

概要

What is Sovereign Debt Crisis?

An MCP (Model Context Protocol) server that provides eight academically‑grounded sovereign debt modeling tools for AI agents and LLM workflows. It integrates live data from 15 sources across macroeconomic databases, trade flows, exchange rates, regulatory feeds, and geopolitical intelligence, enabling structured quantitative analysis of sovereign default, contagion, fiscal sustainability, restructuring, speculative attacks, and political transitions.

How to use Sovereign Debt Crisis?

Add the server URL (https://sovereign-debt-crisis-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN) to your MCP client configuration (Claude Desktop, Cursor, Windsurf, or any MCP‑compatible client). No coding is required—after authentication you can query in plain language (e.g., “model default risk for Turkey”) and the server handles data fetching and computation.

Key features of Sovereign Debt Crisis

  • Eaton‑Gersovitz value function iteration for endogenous default thresholds
  • Eisenberg‑Noe clearing with CDS circularity for bank‑sovereign networks
  • Hansen panel threshold regression for fiscal sustainability breakpoints
  • Myerson mechanism design with Nash‑Rubinstein bargaining for restructuring
  • Morris‑Shin global games resolving speculative attack multiple equilibria
  • MIDAS regression with Almon polynomial lags for multi‑frequency forecasting
  • 5‑minute in‑memory network cache per session
  • 15 integrated live data actors (IMF, World Bank, FRED, OECD, etc.)

Use cases of Sovereign Debt Crisis

  • Sovereign default risk assessment by fixed‑income analysts using live debt/GDP data
  • Bank‑sovereign doom loop analysis for European stress tests and financial stability
  • Fiscal sustainability regime detection for IMF program designers and EM funds
  • Debt restructuring design and negotiation with optimal haircut schedules
  • Currency peg defense and speculative attack modeling for FX strategists

よくある質問

1

What data sources does the server use?

The server pulls live data from 15 sources across five categories: macroeconomic databases (IMF, World Bank, FRED, BLS, OECD, Eurostat), bilateral trade flows (UN COMTRADE, World Bank Projects), exchange rates (current, historical, ECB), regulatory feeds (Federal Register, Congress Bills), and geopolitical intelligence (OpenSanctions, REST Countries). Derived series (CDS spreads, lending exposures, political regime classifications) are computed from these sources.

2

How is authentication handled?

Include your Apify API token either in the server URL as a query parameter (`?token=YOUR_APIFY_TOKEN`) or in the `Authorization` header of the MCP client configuration.

3

Does the server cache data?

Yes. It uses a 5‑minute in‑memory cache that builds the sovereign debt network once per session. All tool calls within the TTL window reuse the cached network without redundant data fetches.

4

What transport and runtime requirements exist?

The server is hosted as an Apify actor and exposes an MCP endpoint via URL. Clients must support the MCP protocol (HTTP/SSE transport). No local installation or additional runtime dependencies are needed beyond an MCP‑compatible client (Claude Desktop, Cursor, Windsurf, etc.).

5

Are there spending or rate limits?

Every tool call checks `Actor.charge()` and stops cleanly if the session budget is reached. The server parallel‑fetches all 15 data sources using `Promise.all` for maximum throughput, but explicitly enforces spending limits on each invocation.

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