SERVE AI Platform

A multi-agent volunteer management platform designed to support the lifecycle of volunteers and needs in the SERVE ecosystem. Built as a Digital Public Good aligned with DPGA.

Architecture

┌─────────────────────────────────────────────────────────────────────────┐
│                          SERVE AI Platform                               │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                          │
│  ┌──────────────┐                                                       │
│  │ serve-ai-ui  │  React Frontend                                       │
│  │  Port 3000   │                                                       │
│  └──────┬───────┘                                                       │
│         │ HTTP                                                          │
│         ▼                                                               │
│  ┌──────────────────┐                                                   │
│  │ serve-orchestrator│  Coordination Layer                              │
│  │    Port 8001      │                                                   │
│  └──────┬───────────┘                                                   │
│         │ HTTP                                                          │
│         ▼                                                               │
│  ┌────────────────────────────┐                                         │
│  │ serve-onboarding-agent-    │  Onboarding Agent                       │
│  │ service    Port 8002       │  (future agents added here)             │
│  └──────┬─────────────────────┘                                         │
│         │ HTTP                                                          │
│         ▼                                                               │
│  ┌────────────────────────────┐         ┌─────────────┐                 │
│  │ serve-agentic-mcp-service  │────────▶│  PostgreSQL │                 │
│  │        Port 8003           │         │  Port 5432  │                 │
│  │   MCP Capabilities + DB    │         └─────────────┘                 │
│  └────────────────────────────┘                                         │
│                                                                          │
└─────────────────────────────────────────────────────────────────────────┘

Project Structure

/app/
├── serve-ai-ui/                      # React Frontend
│   ├── src/
│   ├── public/
│   ├── package.json
│   └── Dockerfile
│
├── serve-orchestrator/               # Coordination Service
│   ├── app/
│   │   ├── api/
│   │   ├── service/
│   │   ├── schemas/
│   │   └── clients/
│   ├── main.py
│   ├── requirements.txt
│   └── Dockerfile
│
├── serve-onboarding-agent-service/   # Onboarding Agent
│   ├── app/
│   │   ├── api/
│   │   ├── service/
│   │   ├── schemas/
│   │   └── clients/
│   ├── main.py
│   ├── requirements.txt
│   └── Dockerfile
│
├── serve-agentic-mcp-service/        # MCP + Database
│   ├── app/
│   │   ├── api/
│   │   ├── service/
│   │   ├── schemas/
│   │   ├── models/
│   │   └── db/
│   ├── main.py
│   ├── requirements.txt
│   └── Dockerfile
│
├── docker-compose.yml                # All services + Postgres
├── .env.example                      # Environment template
└── README.md

Services

Service	Port	Description
serve-ai-ui	3000	React frontend with role-based views
serve-orchestrator	8001	Central coordination layer
serve-onboarding-agent-service	8002	Onboarding agent with LLM
serve-agentic-mcp-service	8003	MCP capabilities + database
postgres	5432	PostgreSQL with persistent volume

Quick Start

Prerequisites

• Docker & Docker Compose

Running

# Clone the repository
git clone <repo-url>
cd serve-ai

# Create environment file
cp .env.example .env
# Edit .env and add your EMERGENT_LLM_KEY

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f

# Access the application
open http://localhost:3000

Stop Services

docker-compose down

Reset Database

docker-compose down -v  # Removes volumes
docker-compose up -d

Service Responsibilities

serve-orchestrator

• Channel-agnostic coordination layer
• Receives interaction requests from UI or channel adapters
• Resolves or creates sessions via MCP
• Determines workflow and active agent
• Routes requests to agent services via HTTP
• Does NOT perform conversational logic
• Does NOT access database directly

serve-onboarding-agent-service

• Implements onboarding conversational logic
• Receives session context from orchestrator
• Generates responses using LLM (Claude Sonnet 4.5)
• Calls MCP capabilities over HTTP
• Returns structured agent responses
• Does NOT access database directly

serve-agentic-mcp-service

• Exposes domain capabilities as HTTP APIs
• Owns ALL database access and persistence
• Stores sessions, profiles, messages, events
• Returns structured capability responses

serve-ai-ui

• React frontend with Tailwind CSS
• Role-based views (Volunteer, Ops, Admin)
• Calls orchestrator via HTTP

API Endpoints

Orchestrator (http://localhost:8001/api)

Endpoint	Method	Description
/interact	POST	Process chat interaction
/session/{id}	GET	Get session state
/sessions	GET	List all sessions
/health	GET	Health check

Onboarding Agent (http://localhost:8002/api)

Endpoint	Method	Description
/turn	POST	Process agent turn
/health	GET	Health check

MCP Service (http://localhost:8003/api/capabilities/onboarding)

Endpoint	Method	Description
/start-session	POST	Create new session
/resume-context	POST	Resume existing session
/advance-state	POST	Advance to next state
/save-confirmed-fields	POST	Save profile fields
/get-missing-fields	POST	Get missing required fields
/save-message	POST	Save conversation message
/log-event	POST	Log telemetry event
/session/{id}	GET	Get full session
/sessions	GET	List all sessions
/telemetry/{id}	GET	Get telemetry events

Database Schema

Core Tables

Table	Description
sessions	Interaction lifecycle tracking
session_events	State transitions and routing
volunteer_profiles	Volunteer information
conversation_messages	Chat history
memory_summaries	Long-term context
handoff_events	Agent transitions
telemetry_events	Operational telemetry

Onboarding States

State	Description
init	Initial welcome
intent_discovery	Understanding motivation
purpose_orientation	Introducing SERVE
eligibility_confirmation	Gathering basic info
capability_discovery	Exploring skills
profile_confirmation	Reviewing info
onboarding_complete	Finished
paused	Session paused

Environment Variables

Root (.env)

EMERGENT_LLM_KEY=your-key-here

serve-orchestrator

Variable	Description
MCP_SERVICE_URL	URL to MCP service
ONBOARDING_AGENT_URL	URL to onboarding agent
CORS_ORIGINS	Allowed CORS origins

serve-onboarding-agent-service

Variable	Description
MCP_SERVICE_URL	URL to MCP service
LLM_PROVIDER	LLM provider (claude/openai/gemini)
LLM_MODEL	Model name
EMERGENT_LLM_KEY	LLM API key

serve-agentic-mcp-service

Variable	Description
DATABASE_URL	PostgreSQL connection string
CORS_ORIGINS	Allowed CORS origins

Adding Future Agents

To add a new agent (e.g., Selection Agent):

1. Create serve-selection-agent-service/ following the onboarding pattern
2. Add service to docker-compose.yml
3. Register agent URL in orchestrator's agent client
4. Implement MCP capabilities for the new domain

Tech Stack

• Frontend: React, Tailwind CSS, shadcn/ui
• Backend: Python 3.11, FastAPI
• Database: PostgreSQL with SQLAlchemy
• LLM: Claude Sonnet 4.5 (configurable)
• Infrastructure: Docker Compose

License

Digital Public Good - DPGA Aligned