A minimal starter template for building multi-agent applications with A2A Protocol (Agent-to-Agent) and AG-UI Protocol (Agent-UI). This project demonstrates how to coordinate multiple AI agents across different frameworks (LangGraph and Google ADK) to solve tasks collaboratively.
- Node.js 18+
- Python 3.10+
- Google API Key - Get one here
- OpenAI API Key - Get one here
- Install frontend dependencies:
npm install
- Install Python dependencies:
cd agents
python3 -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
cd ..
- Set up environment variables:
cp .env.example .env
# Edit .env and add your API keys:
# GOOGLE_API_KEY=your_google_api_key
# OPENAI_API_KEY=your_openai_api_key
- Start all services:
npm run dev
This will start:
- UI: http://localhost:3000
- Orchestrator: http://localhost:9000
- Research Agent: http://localhost:9001
- Analysis Agent: http://localhost:9002
Try asking:
- "Research quantum computing"
- "Tell me about artificial intelligence"
- "Research renewable energy"
The orchestrator will:
- Send your query to the Research Agent to gather information
- Pass the research to the Analysis Agent for insights
- Present a complete summary with both research and analysis
# Start everything
npm run dev
# Start individual services
npm run dev:ui # Next.js UI only
npm run dev:orchestrator # Orchestrator only
npm run dev:research # Research agent only
npm run dev:analysis # Analysis agent only
# Build for production
npm run build
# Lint code
npm run lint
-
Create a new Python agent in
agents/
:- Implement A2A Protocol (see existing agents as examples)
- Choose a port (e.g., 9003)
- Define agent capabilities and skills
-
Register in middleware (
app/api/copilotkit/route.ts
):const newAgentUrl = "http://localhost:9003"; const a2aMiddlewareAgent = new A2AMiddlewareAgent({ agentUrls: [ researchAgentUrl, analysisAgentUrl, newAgentUrl, // Add here ], // ... });
-
Add run script in
package.json
:"dev:newagent": "python3 agents/new_agent.py"
-
Update concurrently command to include your new agent
- Main page: Edit
app/page.tsx
for layout and result display - Chat: Edit
components/chat.tsx
for chat behavior - Styling: Edit
app/globals.css
andtailwind.config.ts
- A2A badges: Edit
components/a2a/
components
This starter shows how specialized agents built with different frameworks can communicate via the A2A protocol:
┌──────────────────────────────────────────┐
│ Next.js UI (CopilotKit) │
└────────────┬─────────────────────────────┘
│ AG-UI Protocol
┌────────────┴─────────────────────────────┐
│ A2A Middleware │
│ - Routes messages between agents │
└──────┬───────────────────────────────────┘
│ A2A Protocol
│
├─────► Research Agent (LangGraph)
│ - Gathers information
│ - Port 9001
│
└─────► Analysis Agent (ADK)
- Analyzes findings
- Port 9002
▲
│
┌──────┴──────────┐
│ Orchestrator │
│ (ADK) │
│ Port 9000 │
└─────────────────┘
-
Orchestrator (ADK + AG-UI Protocol)
- Receives requests from the UI
- Coordinates specialized agents
- Port: 9000
-
Research Agent (LangGraph + A2A Protocol)
- Gathers and summarizes information
- Returns structured JSON
- Port: 9001
-
Analysis Agent (ADK + A2A Protocol)
- Analyzes research findings
- Provides insights and conclusions
- Port: 9002
starter/
├── app/
│ ├── api/copilotkit/route.ts # A2A middleware setup (KEY FILE!)
│ ├── layout.tsx # Root layout
│ ├── globals.css # Styles
│ └── page.tsx # Main UI
│
├── components/
│ ├── chat.tsx # Chat component with A2A visualization
│ └── a2a/ # A2A message components
│ ├── agent-styles.ts # Agent branding utilities
│ ├── MessageToA2A.tsx # Outgoing message badges
│ └── MessageFromA2A.tsx # Incoming message badges
│
├── agents/ # Python agents
│ ├── orchestrator.py # Orchestrator (ADK + AG-UI) - Port 9000
│ ├── research_agent.py # Research (LangGraph + A2A) - Port 9001
│ ├── analysis_agent.py # Analysis (ADK + A2A) - Port 9002
│ └── requirements.txt # Python dependencies
│
├── package.json # Frontend dependencies & scripts
├── .env.example # Environment variables template
└── README.md # This file
The AG-UI Protocol standardizes communication between the frontend (CopilotKit) and agents. The orchestrator uses AG-UI to receive messages from the UI.
The A2A Protocol standardizes agent-to-agent communication. The Research and Analysis agents use A2A to communicate with the orchestrator.
The A2A Middleware (in app/api/copilotkit/route.ts
) is the magic that connects everything:
- Wraps the orchestrator agent
- Registers A2A agents automatically
- Injects a
send_message_to_a2a_agent
tool into the orchestrator - Routes messages between agents
- Verify all services are running:
http://localhost:9000-9002
- Check console for startup errors
- Ensure
.env
file exists withGOOGLE_API_KEY
andOPENAI_API_KEY
- Restart all services after adding keys
- Activate virtual environment:
source agents/.venv/bin/activate
- Reinstall dependencies:
pip install -r agents/requirements.txt
- Change ports in
.env
file:ORCHESTRATOR_PORT=9000 RESEARCH_PORT=9001 ANALYSIS_PORT=9002
- AG-UI Protocol Documentation
- A2A Protocol Specification
- Google ADK Documentation
- LangGraph Documentation
- CopilotKit Documentation
MIT