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Political Influence Network 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

Political Influence Network MCP Server について

Political influence network analysis for AI assistants — map donor-politician-legislation relationships, detect conflicts of interest, and trace dark money flows through 8 US government data sources in a single MCP tool call.

Political Influence Network 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": {
    "political-influence-network-mcp": {
      "url": "https://ryanclinton--political-influence-network-mcp.apify.actor/mcp"
    }
  }
}

Political Influence Network 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 Political Influence Network?

Political Influence Network is an MCP server that maps donor-politician-legislation relationships, detects conflicts of interest, and traces dark money flows across eight US government data sources. It is built for compliance teams, investigative researchers, and AI agents needing structured political intelligence without raw API complexity.

How to use Political Influence Network?

Add the server URL to your MCP client (Claude Desktop, Cursor, Windsurf) using the configuration shown in the README. No API key is required. Then call any of the eight MCP tools with a query string and optional source filters; each tool returns structured JSON with scored entities and findings.

Key features of Political Influence Network

  • PageRank influence scoring on the full political graph
  • Bipartite graph construction with 8 node and 7 edge types
  • Temporal Granger causality for donation-to-legislation links
  • Conflict of interest detection across stock trades and legislation
  • Dark money path tracing through nonprofit intermediaries
  • Revolving door analysis with influence potential scoring
  • Lobbying ROI calculation (legislative wins per dollar spent)
  • Multi-factor political risk scoring (6 weighted factors)
  • 5‑minute TTL cache to avoid redundant API costs
  • Supports both SSE and Streamable HTTP transports

Use cases of Political Influence Network

  • Corporate political risk assessment for compliance and ESG teams
  • Investigative journalism into regulatory capture or pay-to-play contracting
  • Lobbying effectiveness benchmarking for trade associations and corporations
  • Congressional trading oversight for ethics watchdogs and investors
  • AI agent political intelligence workflows for due diligence and monitoring
  • Nonprofit and dark money investigations via multi-hop funding tracing

よくある質問

1

What data sources does Political Influence Network use?

It orchestrates eight public data actors in parallel: FEC campaign finance filings, congressional stock trading disclosures, Congress.gov bill tracking, Federal Register regulatory actions, nonprofit organization filings, USAspending federal contracts, OpenCorporates corporate registries, and Wikipedia background context.

2

How do I connect my MCP client?

Add the server URL `https://ryanclinton--political-influence-network-mcp.apify.actor/mcp` to your client’s MCP configuration. No API key is required; the server runs on Apify’s infrastructure.

3

What tools are available and what do they cost?

Eight tools are provided: `map_influence_network`, `detect_conflict_of_interest`, `trace_money_to_legislation`, `analyze_revolving_door`, `score_lobbying_influence`, `detect_dark_money_flows`, `compute_political_risk_score`, and `generate_influence_report`. Each tool costs $0.045 or $0.050 per call.

4

What input parameters do the tools accept?

Each tool accepts a required `query` string (politician, corporation, PAC, or policy topic) and an optional `sources` array to select specific data groups (e.g., `"finance"`, `"trading"`, `"legislation"`). Default sources vary by tool.

5

What are the limits and caching behavior?

Each upstream actor is called with a 500‑item limit and a 180‑second timeout; failed sources return empty arrays without crashing. All actor calls are cached for 5 minutes per query to avoid redundant API costs.

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