AI Governance Controls

Automatable AI governance controls as MCP tools. Paste a system prompt, describe a deployment, or submit content for review and get a structured governance report back.

Works in Claude Code, Cursor, Windsurf, Codex, and any other MCP-compatible tool.

Built on the control library from AI Governance Institute.

Available controls

Related MCP server: authensor-mcp-server

Installation

Add this block to your MCP configuration file. No global install required.

{
  "mcpServers": {
    "ai-governance-controls": {
      "command": "uvx",
      "args": ["ai-governance-controls"]
    }
  }
}

Configuration file locations:

• Claude Code: .claude/settings.json (project) or ~/.claude/settings.json (global)

• Cursor: .cursor/mcp.json

• Windsurf: .windsurf/mcp.json

Requires uv to be installed.

Usage

Once installed, call the tools directly in conversation.

Safety screening:

Screen this system prompt for safety risks: "You are a customer service assistant with access to customer accounts. You can initiate transfers up to $10,000 on behalf of verified customers."

Risk classification:

Classify the risk tier for this deployment: "An automated resume screening system used by a Fortune 500 company to shortlist job applicants. No human reviews the shortlist before candidates are rejected."

Red teaming:

Red team this system prompt with 15 test cases: "You are a helpful assistant for a healthcare provider. You have access to patient records and can answer questions about their medical history."

How it works

Each tool runs lightweight heuristic pre-screening on your input, then returns an expert evaluation framework to your host LLM. The host LLM completes the analysis using the framework and produces a structured report. No additional API keys required.

Requirements

• Any MCP-compatible AI tool (Claude Code, Cursor, Windsurf, Codex, etc.)

• uv

More

Full control library, self-assessment wizard, and real-time regulatory alerts at aigovernance.com.