A2a Adk MCP Example

🚀 AI Agent Project with Google ADK, A2A Protocol and MCP Integration

This project is an implementation of an AI agent integrated with Google ADK (Agent Development Kit). It supports the A2A (Agent-to-Agent) protocol for interacting with other agents and can be extended through MCP (Model Context Protocol) servers. The project includes a ready-made infrastructure for developing, testing, and deploying AI agents with monitoring and tracing capabilities.

Detailed documentation about the A2A protocol: Documentation and Postman Collection

✨ Features

• Google ADK Integration - Utilize the advanced SDK for agent development.
• MCP Tools Support - Integrate with the Model Context Protocol for extensible tools.
• LiteLLM - Support various LLM models through a unified interface.
• Phoenix Monitoring - Optional monitoring and tracing of execution.
• Docker Ready - Fully containerized with automatic configuration.
• A2A Protocol - Agent-to-Agent communication.
• Flexible Configuration - Configure via environment variables.

📁 Project Structure

a2a-adk-mcp-example/
├── agent/                  # Agent directory
│   ├── app/                # Main application code
│   │   ├── __main__.py     # Entry point with Click CLI
│   │   ├── agent.py        # AgentEvolution class
│   │   └── agent_executor.py  # Agent executor
│   ├── .env.example        # Example configuration file
│   ├── pyproject.toml      # Project configuration and dependencies
│   └── README.md           # Agent documentation
├── mcp-weather/            # MCP weather server
│   ├── server.py           # Main server
│   ├── Dockerfile          # Docker configuration
│   └── README.md           # MCP server documentation
├── nginx/                  # Nginx configuration
├── docker-compose.phoenix.yml  # Configuration with Phoenix
├── docker-compose.yml      # Main Docker Compose configuration
├── Makefile                # Command automation
└── .gitignore              # Ignored files

🚀 Quick Start

Quick Start with Docker (Recommended)

# Build images
make build

# Start main services
make up

# The agent will be available at http://localhost:10002
# The MCP server will be available at http://localhost:8001

Using Makefile

# View all available commands
make help

# Start main services
make up

# Start with Phoenix monitoring
make phoenix

# Development mode
make dev

# View logs
make logs

# Stop all services
make down

🔧 Configuration

Create an Environment File

# Create a .env file from the example
make env

# Or manually
cp agent/.env.example .env

Main Environment Variables

The following parameters can be configured in the .env file:

# Main agent settings
AGENT_NAME=jira_mcp_agent
AGENT_DESCRIPTION="Jira MCP agent for project, task, sprint, and agile process management"
AGENT_VERSION=1.0.0

# Model configuration
LLM_MODEL="evolution_inference/model-for-agent-space-test"
LLM_API_BASE="https://your-model-api-base-url/v1"

# MCP Configuration
MCP_URL=http://mcp-weather:8001/sse

# Phoenix monitoring (optional)
PHOENIX_PROJECT_NAME="ip_agent_adk"
PHOENIX_ENDPOINT="http://phoenix:6006/v1/traces"

# Server settings
HOST="0.0.0.0"
PORT="10002"

# Monitoring
ENABLE_PHOENIX="false"
ENABLE_MONITORING="true"

💻 Usage Examples

Start the Agent

# Start main services
make up

# The agent will be available at http://localhost:10002

Development Mode

# Start in development mode with live reload
make dev

# Start with Phoenix monitoring for debugging
make dev-phoenix

Check Status

# Status of all services
make status

# Health check
make health

# View logs
make logs

Components of the Project

Agent (agent/)

The main component of the project is an AI agent based on Google ADK, supporting MCP tools. The agent implements the A2A Protocol for interacting with other agents.

API Endpoints

• GET / - Agent information (Agent Card)
• POST /tasks - Create a new task
• GET /tasks/{task_id} - Get the status of a task
• GET /tasks/{task_id}/stream - SSE stream of task execution

MCP Weather Server (mcp-weather/)

The server provides tools for obtaining weather data through the MCP protocol. It uses the free Open-Meteo API.

Tools

• get_today_weather(city: str) - Get today's current weather for the specified city
• get_weekly_forecast(city: str) - Get the weekly weather forecast for the specified city

Endpoints

• SSE: http://localhost:8001/sse
• Messages: http://localhost:8001/messages/

📊 Monitoring

Phoenix Tracing

To enable Phoenix monitoring, set the environment variable:

ENABLE_PHOENIX=true

Start with Phoenix:

make phoenix

The Phoenix Dashboard will be available at http://localhost:6006

🐳 Docker Commands

# Main commands
make build          # Build images
make up            # Start services
make down          # Stop services
make restart       # Restart
make logs          # View logs

# Phoenix monitoring
make phoenix       # Start with monitoring
make phoenix-down  # Stop Phoenix

# Utilities
make shell         # Enter the agent container
make clean         # Clean Docker resources

📋 Requirements

• Docker: For containerization
• Make: For command automation
• MCP Server: For tools (optional)

📄 License

This project is distributed under the MIT license. See the LICENSE file for details (if available).

🔗 Useful Links

• Google ADK Documentation
• Model Context Protocol
• LiteLLM Documentation
• Phoenix Tracing