Quickstart

This guide walks you through connecting your site to Inception Agents and verifying your first agent interaction. Total setup time: under 10 minutes.

1. Create Your Account

Sign up at inceptionagents.com. You will need a work email and your site’s domain. Free trials include full access to detection, optimization, and analytics.

2. Add Your Domain

From the dashboard, navigate to Settings > Domains and add your production domain:

example.com

Inception Agents will run an initial crawl to analyze your existing content structure, metadata, and schema markup. This typically completes within a few minutes.

3. Choose Your Integration Method

Inception Agents operates at the edge, intercepting requests before they reach your origin server. Choose the integration that matches your stack:

Integration	Best For	Setup Time
Shopify App	Shopify and Shopify Plus stores	~2 min
Vercel Middleware	Next.js apps deployed on Vercel	~3 min
Cloudflare Worker	Any site proxied through Cloudflare	~5 min
Express Middleware	Node.js/Express backends	~5 min
WordPress Plugin	WordPress and WooCommerce sites	~2 min
Universal JS Snippet	Any website, any stack	~3 min

Shopify App

Install directly from the Shopify App Store. The app injects edge middleware automatically — no code changes required. Handles product feeds, structured data, and llms.txt generation out of the box.

See the full Shopify Integration Guide for theme customization and Shopify Flow triggers.

Vercel Middleware

Add the @inceptionagents/vercel package and configure your middleware.ts:

npm install @inceptionagents/vercel

// middleware.ts
import { createMiddleware } from '@inceptionagents/vercel';

export default createMiddleware({
  siteId: 'your-site-id',
});

export const config = {
  matcher: ['/((?!_next/static|_next/image|favicon.ico).*)'],
};

See the full Vercel Integration Guide for edge config, A/B testing, and ISR compatibility.

Cloudflare Worker

Deploy the worker from your dashboard or use Wrangler:

npm install @inceptionagents/cloudflare

// src/index.ts
import { handleRequest } from '@inceptionagents/cloudflare';

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    return handleRequest(request, {
      siteId: env.INCEPTION_SITE_ID,
      upstream: env.ORIGIN_URL,
    });
  },
};

See the full Cloudflare Integration Guide for KV caching, custom rules, and Workers Routes setup.

Express Middleware

Add the middleware to your Express app:

npm install @inceptionagents/express

const { inceptionAgents } = require('@inceptionagents/express');

app.use(inceptionAgents({
  siteId: 'your-site-id',
}));

See the full Express Integration Guide for custom route handling and response streaming.

WordPress Plugin

Install the plugin from Plugins > Add New by searching “Inception Agents,” or upload the .zip from your dashboard. Enter your Site ID in Settings > Inception Agents and activate.

See the full WordPress Integration Guide for WooCommerce product sync and cache plugin compatibility.

Universal JS Snippet

For any other platform, add the script tag to your site’s <head>:

<script
  src="https://cdn.inceptionagents.com/agent-edge.js"
  data-site-id="your-site-id"
  defer
></script>

This runs client-side detection and redirects agent requests through the Inception Agents edge network. It works on any stack but has slightly higher latency than server-side integrations.

See the full Universal Snippet Guide for SPA support and custom event hooks.

4. Verify Your Integration

Once deployed, verify that agent detection is working. Use curl to simulate an agent request:

# Simulate a GPTBot request
curl -H "User-Agent: Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko); compatible; GPTBot/1.0" \
  https://example.com/

# Check your llms.txt file
curl https://example.com/llms.txt

# Check your agent card
curl https://example.com/.well-known/agent.json

A successful response from the first command will include the X-Inception-Agent header:

X-Inception-Agent: detected
X-Inception-Agent-Platform: openai
X-Inception-Agent-Type: gptbot

The llms.txt request should return a markdown document describing your site. The agent.json request should return a JSON object declaring your site’s capabilities.

5. Check Your Dashboard

Navigate to the Analytics tab in your dashboard. Within minutes of deploying, you should see:

Agent Detection Events — real-time log of detected agent visits
Content Served — which optimized content variants were returned
Platform Breakdown — traffic split across ChatGPT, Claude, Perplexity, Gemini, Copilot, Rufus, and Grok

If you do not see any events after 15 minutes, check the Troubleshooting Guide.

6. What to Expect

After integration, the platform begins working immediately:

Timeframe	What Happens
0–1 hour	Initial content analysis completes. Your existing pages are indexed and scored for agent readability.
1–6 hours	`llms.txt` and `agent.json` files are generated and served. Structured data gaps are identified.
6–24 hours	First optimization pass runs. Content variants are generated for detected agent intents. JSON-LD enrichment is applied.
24–72 hours	Learning engine activates. The platform begins adapting content strategies based on observed agent behavior.
1 week+	Continuous optimization. Content variants are refined, new agent patterns are detected, and recommendations improve.

Next Steps

Core Concepts — understand how the three systems (detection, optimization, learning) work together
How Agents Evaluate — learn what each AI platform prioritizes when evaluating your content
llms.txt Reference — customize your machine-readable site description
Dashboard Guide — get the most out of your analytics and optimization controls