guardrail-sim
byJeff Green

Getting Started

Set up guardrail-sim in your project

Getting Started

Install guardrail-sim and evaluate your first policy in 5 minutes.

Installation

# Core policy engine
npm install @guardrail-sim/policy-engine
 
# MCP server for AI agent integration
npm install @guardrail-sim/mcp-server
 
# Optional: UCP types for TypeScript
npm install @guardrail-sim/ucp-types
 
# Optional: Policy insights and health checks
npm install @guardrail-sim/insights

Your First Policy Evaluation

The policy engine evaluates discount requests against rules:

import { PolicyEngine, defaultPolicy } from '@guardrail-sim/policy-engine';
import type { Order } from '@guardrail-sim/policy-engine';
 
// Create engine with default policy
const engine = new PolicyEngine(defaultPolicy);
 
// Define an order
const order: Order = {
  order_value: 5000,      // $5,000 order
  quantity: 100,          // 100 units
  product_margin: 0.4,    // 40% base margin
  customer_segment: 'gold'
};
 
// Evaluate a 12% discount request
const result = await engine.evaluate(order, 0.12);
 
console.log(result);
// {
//   approved: true,
//   violations: [],
//   triggeredRules: ['margin_floor', 'max_discount'],
//   calculated_margin: 0.28
// }

Default Policy Rules

The default policy includes these rules:

RuleDescriptionLimit
margin_floorMinimum margin after discount15%
max_discountMaximum allowed discount25%
volume_tierVolume-based discount limits10% base, 15% for 100+ units

Custom Policies

Create your own policy with custom rules:

import { PolicyEngine } from '@guardrail-sim/policy-engine';
import type { Policy } from '@guardrail-sim/policy-engine';
 
const customPolicy: Policy = {
  id: 'holiday-2026',
  name: 'Holiday Sale Policy',
  description: 'Special limits for holiday promotions',
  rules: [
    {
      id: 'holiday-max',
      name: 'Holiday Max Discount',
      priority: 1,
      conditions: { all: [] },
      event: {
        type: 'max_discount',
        params: { limit: 0.30 }  // 30% max
      }
    }
  ]
};
 
const engine = new PolicyEngine(customPolicy);

Using with MCP

For AI agent integration, run the MCP server:

# Start the MCP server
npx guardrail-mcp

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "guardrail-sim": {
      "command": "npx",
      "args": ["guardrail-mcp"]
    }
  }
}

The MCP server exposes 5 tools:

  • evaluate_policy - Evaluate discount against policy
  • get_policy_summary - Get human-readable policy rules
  • get_max_discount - Calculate maximum allowed discount
  • validate_discount_code - UCP-aligned pre-validation
  • simulate_checkout_discount - Full checkout simulation

Next Steps

On this page