Agent Reference
This page documents the core MuleSoft agents behind the Hushh Agentic Developer APIs.
A2A JSON-RPC 2.0 envelope
{
"jsonrpc": "2.0",
"id": "task-124",
"method": "tasks/send",
"params": {
"sessionId": "session-456",
"message": {
"role": "user",
"parts": [
{
"type": "text",
"text": "Provide a detailed JSON profile for Sundar Pichai, email sundar.pichai@example.com, phone +1 6505559001."
}
]
}
}
}For browser-based testing, use /api/a2a/{agent}. Use direct MuleSoft endpoints from your backend only.
Integration flow in Hushh
- User submits name, email, and phone
- MuleSoft constructs the JSON-RPC request
- Agent responds with a
userProfileJSON payload - DataWeave transforms and stores the profile in Hushh data stores
Error handling
| Code | Description | Resolution |
|---|---|---|
| 400 | Invalid JSON-RPC format | Validate the request body schema |
| 401 | Unauthorized | Check credentials or rotate keys |
| 500 | Internal agent error | Retry with backoff or contact support |
| TIMEOUT | Agent took too long | Reduce payload size or split requests |
OpenAI Public Data Agent
- Purpose: enrich profiles from public signals
- Model: GPT-4.0 mini
- Proxy endpoint:
POST /api/a2a/public - MuleSoft endpoint:
https://hushh-open-ai-agent-app-bubqpu.5sc6y6-3.usa-e2.cloudhub.io/public-data-agent
Sample prompt (Sundar Pichai)
Provide a detailed JSON profile for Sundar Pichai, email sundar.pichai@example.com, phone +1 6505559001.Sample response (trimmed)
{
"jsonrpc": "2.0",
"id": "task-124",
"result": {
"sessionId": "session-456",
"status": {
"state": "completed",
"message": {
"role": "agent",
"parts": [
{
"type": "text",
"text": {
"userProfile": {
"fullName": "Sundar Pichai",
"phone": "+1 6505559001",
"email": "sundar.pichai@example.com",
"city": "Mountain View",
"occupation": "CEO",
"dietPreference": "Vegetarian"
}
}
}
]
}
}
}
}Gemini Public Data Agent
- Purpose: high-confidence enrichment and gap filling
- Model: gemini-2.5-pro
- Proxy endpoint:
POST /api/a2a/gemini - MuleSoft endpoint:
https://hushh-gemini-ai-agent-app-bubqpu.5sc6y6-3.usa-e2.cloudhub.io/public-data-agent
Supabase Profile Creation Agent
- Purpose: create a structured profile from natural language
- Proxy endpoint:
POST /api/a2a/hushh-profile - MuleSoft endpoint:
https://hushh-supabase-agent-app-bubqpu.5sc6y6-2.usa-e2.cloudhub.io/supabase-agent
Example prompt:
Create a profile for Sundar Pichai, email sundar.pichai@example.com, phone +1 6505559001.Supabase Profile Update Agent
- Purpose: update profile fields with natural language
- Proxy endpoint:
POST /api/a2a/hushh-profile-update - MuleSoft endpoint:
https://hushh-supabase-agent-app-bubqpu.5sc6y6-2.usa-e2.cloudhub.io/supabase-agent
Example prompt:
Update the city for Sundar Pichai to Mountain View.Supabase Profile Query Agent
- Purpose: fetch full profiles from Supabase
- Proxy endpoint:
POST /api/a2a/hushh - MuleSoft endpoint:
https://hushh-supabase-query-agent-app-bubqpu.5sc6y6-2.usa-e2.cloudhub.io/supabase-query-agent
Example prompt:
Fetch all details for Sundar Pichai with phone +1 6505559001.Brand User Data Query Agent
- Purpose: retrieve brand preferences and CRM-ready insights
- Model: GPT-4.0 mini
- Proxy endpoint:
POST /api/a2a/brand - MuleSoft endpoint:
https://hushh-brand-agent-app-bubqpu.5sc6y6-4.usa-e2.cloudhub.io/crm-agent
This agent acts as the bridge between brand assistants and CRM data, returning a conversational summary plus structured insights.
Example prompt:
Summarize brand preferences and purchase intents for Sundar Pichai.Example queries
- Fetch all details for Sundar Pichai with phone +1 6505559001.
- Fetch all intents for Sundar Pichai with phone +1 6505559001.
- Fetch all wants and desires for Sundar Pichai with phone +1 6505559001.
- What is the occupation and education level for Sundar Pichai?