DEVELOPER ENVIRONMENT
System Integrations & API Gateway
Connect BrandCheck Pro as a Model Context Protocol (MCP) server or query the compliance broker directly in your CI/CD pipeline.
Authentication Token Manager
Generate a secure, mock JSON Web Token (JWT) credentials string to authenticate your sandbox connections.
LIVE COMPLIANCE CORE VALIDATION
Provision real-time LLM inference checks by connecting your OpenRouter key. Transactions run ephemeral, client-side, and are never saved to servers.
Model Context Protocol (MCP)
BrandCheck Pro can be registered as an MCP server to let AI agents call tools and retrieve real-time regional risk checks automatically. Add this configuration to your client workspace:
{
"mcpServers": {
"brandcheck-mcp": {
"command": "node",
"args": ["/path/to/brandcheck-mcp/index.js"],
"env": {
"BRANDCHECK_API_KEY": "YOUR_TOKEN"
}
}
}
}
REST API CONNECTOR ENDPOINT
cURL Payload Request
curl -X POST "http://localhost:8000/v1/analyze" \
-H "Content-Type: application/json" \
-H "X-BrandCheck-Tier: EnterprisePaid" \
-d '{
"text": "Our sacred festive sale brings you cheap deals!",
"market": "IN-HN"
}'
Python Integration
import requests
payload = {
"text": "Our sacred festive sale brings you cheap deals!",
"market": "IN-HN"
}
headers = {
"Content-Type": "application/json",
"X-BrandCheck-Tier": "EnterprisePaid"
}
response = requests.post("http://localhost:8000/v1/analyze", json=payload, headers=headers)
print(response.json())
Response JSON Schema
{
"overall_score": 65,
"risk_level": "High Risk",
"summary": "Evaluation flagged potential controversy parameters.",
"flagged_issues": [
{
"phrase": "cheap",
"category": "Gender & Social Tone",
"rationale": "Potential risk associated with demographic marginalization."
}
]
}
