Remote Plugins

Run services separately, connect via HTTP

When to Use

✅ AI/ML processing (heavy computation)
✅ Proprietary/commercial logic
✅ Independent scaling needs
✅ External team ownership

❌ Core functionality → Use Direct Plugin
❌ Need custom schema → Use Hybrid Plugin

How It Works

Your Service ←─────HTTP────── Data Pod
     │                            │
     ├─ Register capabilities     │
     ├─ Receive webhook calls     │
     └─ Call back with results ───┘

Build your service (any tech stack)
Register with Intelligence Registry
Receive webhooks from Data Pod
Call back with results

Step-by-Step Tutorial

1. Build Your Service

Any tech stack works. Example with Node.js:

// src/index.ts
import { Hono } from 'hono';
 
const app = new Hono();
 
app.post('/webhook', async (c) => {
  const payload = await c.req.json();
  
  // Your AI/processing logic
  const result = await processData(payload.data);
  
  // Call back to Data Pod
  await fetch(payload.callbackUrl, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      itemId: payload.itemId,
      result
    })
  });
  
  return c.json({ success: true });
});
 
export default { port: 3001, fetch: app.fetch };

2. Register with Intelligence Registry

const response = await fetch('http://datapod/trpc/intelligenceRegistry.register', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    serviceId: 'my-ai-service',
    name: 'My AI Service',
    webhookUrl: 'https://my-service.com/webhook',
    apiKey: process.env.SERVICE_API_KEY,
    capabilities: ['analysis', 'summarization'],
    pricing: 'free',
    version: '1.0.0'
  })
});

3. Implement Webhook Endpoint

Data Pod will call your webhook:

app.post('/webhook', async (c) => {
  // Authenticate
  const apiKey = c.req.header('Authorization')?.replace('Bearer ', '');
  if (apiKey !== process.env.SERVICE_API_KEY) {
    return c.json({ error: 'Unauthorized' }, 401);
  }
  
  // Parse request
  const { itemId, data, callbackUrl } = await c.req.json();
  
  // Process with your AI/logic
  const analysis = await analyzeData(data);
  
  // Call back to Data Pod
  await fetch(callbackUrl, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'X-Webhook-Secret': process.env.CALLBACK_SECRET
    },
    body: JSON.stringify({
      itemId,
      analysis: {
        priority: 'high',
        tags: ['important', 'ai-analyzed'],
        summary: analysis.summary
      }
    })
  });
  
  return c.json({ success: true });
});

4. Handle Callbacks

Data Pod expects results at callback URL:

// What Data Pod expects
{
  itemId: string;
  analysis: {
    priority?: 'urgent' | 'high' | 'normal' | 'low';
    tags?: string[];
    category?: string;
    summary?: string;
  }
}

Discovery

Frontends discover your service:

// Frontend code
const capabilities = await client.capabilities.list();
 
// Find your service
const myService = capabilities.intelligenceServices.find(
  s => s.serviceId === 'my-ai-service'
);

Authentication

Two-way authentication:

Data Pod → Your Service:

headers: {
  'Authorization': `Bearer ${service.apiKey}`
}

Your Service → Data Pod:

headers: {
  'X-Webhook-Secret': process.env.CALLBACK_SECRET
}

Real Example: Life Feed Intelligence

See the complete implementation:

Service: synap-intelligence-service/
Registration: Happens on startup
Webhook: Receives inbox items
Callback: Returns analysis

View example →

Testing Locally

# 1. Start Data Pod
cd synap-backend/apps/api
pnpm dev
 
# 2. Start your service
cd my-service
pnpm dev
 
# 3. Register service
curl -X POST http://localhost:3000/trpc/intelligenceRegistry.register \
  -H "Content-Type: application/json" \
  -d '{"serviceId":"test","webhookUrl":"http://localhost:3001/webhook",...}'
 
# 4. Trigger workflow
curl -X POST http://localhost:3000/webhooks/n8n/inbox \
  -H "X-Webhook-Secret: dev" \
  -d '{"items":[...]}'

Deployment

Deploy your service anywhere:

Cloud: AWS, Google Cloud, Azure
PaaS: Vercel, Railway, Fly.io
Self-hosted: Docker, Kubernetes

Data Pod connects via HTTP - deployment is independent.

Next Steps

Need schema in Data Pod? → Hybrid Plugins
See complete workflow → Unified feed (team docs)
Learn Intelligence Registry → Intelligence Registry Guide

Remote Plugins

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