a2a-adk-mcp-example

# AI Agent Project with Google ADK, A2A Protocol and MCP Integration This project represents an implementation of an AI agent with integration of Google ADK (Agent Development Kit), supporting the A2A (Agent-to-Agent) protocol for interaction with other agents and extensible through MCP (Model Context Protocol) servers. The project includes a ready-made infrastructure for developing, testing, and deploying AI agents with monitoring and tracing. Detailed documentation on the A2A protocol: [documentation](./documentation-a2a-russian.md) and [Postman collection](./postman-collection-a2a-spec.json) ## 🎯 Features - **Google ADK Integration** - Utilizing a state-of-the-art SDK for agent development - **MCP Tools Support** - Integration with Model Context Protocol for extensible tools - **LiteLLM** - Support for various LLM models through a unified interface - **Phoenix Monitoring** - Optional monitoring and tracing of execution - **Docker Ready** - Full containerization with automatic setup - **A2A Protocol** - Agent-to-Agent communication - **Flexible Configuration** - Configuration through environment variables ## 📁 Project Structure ``` a2a-adk-mcp-example/ ├── agent/ # Agent directory │ ├── app/ # Main application code │ │ ├── __main__.py # Entry point with Click CLI │ │ ├── agent.py # Class AgentEvolution │ │ └── agent_executor.py # Agent executor │ ├── .env.example # Example configuration file │ ├── pyproject.toml # Project configuration and dependencies │ └── README.md # Agent documentation ├── mcp-weather/ # Weather MCP 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 ``` ## 🛠 Installation and Quick Start ### Quick Start with Docker (recommended) ```bash # 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 ```bash # 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 ### Creating the Environment File ```bash # Create .env file from example make env # Or manually cp agent/.env.example .env ``` ### Main Environment Variables In the `.env` file, you can configure the following parameters: ```bash # Main agent settings AGENT_NAME=jira_mcp_agent AGENT_DESCRIPTION="Jira MCP agent for managing projects, tasks, sprints, and agile processes" 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 ### Running the Agent ```bash # Start main services make up # The agent will be available at http://localhost:10002 ``` ### Development Mode ```bash # Run in development mode with live reload make dev # Run with Phoenix monitoring for debugging make dev-phoenix ``` ### Checking Status ```bash # Status of all services make status # Health check make health # View logs make logs ``` ## 🧩 Project Components ### Agent (agent/) The main component of the project is the AI agent based on Google ADK with support for MCP tools. The agent implements the A2A Protocol for interaction with other agents. #### API Endpoints - `GET /` - Information about the agent (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 ### Weather MCP 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)` - Gets the current weather for today for the specified city - `get_weekly_forecast(city: str)` - Gets 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: ```bash ENABLE_PHOENIX=true ``` Run with Phoenix: ```bash make phoenix ``` The Phoenix Dashboard will be available at http://localhost:6006 ## 🐳 Docker Commands ```bash # 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 up Docker resources ``` ## 📋 Requirements - **Docker**: For containerization - **Make**: For command automation - **MCP Server**: For tools (optional) ## 📄 License This project is licensed under the MIT License. See the `LICENSE` file for details (if available). ## 🔗 Useful Links - [Google ADK Documentation](https://developers.google.com/adk) - [Model Context Protocol](https://modelcontextprotocol.io/) - [LiteLLM Documentation](https://docs.litellm.ai/) - [Phoenix Tracing](https://phoenix.arize.com/)