ai-model-governance-mcp

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

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

{
  "mcpServers": {
    "ai-model-governance-mcp": {
      "url": "https://ryanclinton--ai-model-governance-mcp.apify.actor/mcp"
    }
  }
}

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AI model governance intelligence for AI agents, compliance teams, and legal counsel — delivered via the Model Context Protocol. This MCP server gives your AI agent live access to US federal regulations, congressional AI bills, EU AI Act signals, academic safety research, and open-source audit tooling through 8 purpose-built tools that score, classify, and explain the AI governance landscape.

Built for Chief AI Officers, responsible AI teams, and compliance engineers who need regulatory intelligence integrated directly into their AI workflows. Every tool returns structured JSON with scores, evidence signals, and actionable recommendations — no manual research, no dashboard subscriptions.

| Data Point | Source | Example | |-----------|--------|---------| | 📋 US federal AI regulations and executive orders | Federal Register | "Artificial Intelligence in Federal Agencies — Proposed Rule" | | 🏛️ AI-specific congressional bills and status | Congress Bills | "Algorithmic Accountability Act — Committee review" | | 🇪🇺 EU AI Act implementation and digital economy metrics | Eurostat | EU member state AI adoption indicators | | 🔬 Pre-publication AI safety and alignment research | ArXiv Preprints | "RLHF alignment failures in foundation models" | | 📚 Peer-reviewed AI fairness and bias literature | Semantic Scholar | "Disparate impact in automated hiring systems" | | 🛠️ Open-source AI audit and bias detection tools | GitHub Repositories | fairlearn, AIF360, OpenAI evals, model cards | | 📡 AI polic