Google ADK Development Environment
About
MCP (Model Context Protocol) development environment with Google ADK Python framework integration and custom network discovery server
Explore
- Port Forwarding - Common development ports (3000, 5000, 8000, 8080, 9000)
- Custom Aliases - Helpful shortcuts for ADK development
- Auto-formatting - Code formatting on save
- Testing Setup - pytest configuration
- Jupyter Support - For interactive development
This project is set up with a development container optimized for Google Agent Development Kit (ADK) development using Python 3.13.
1. Prerequisites: Make sure you have VS Code with the Dev Containers extension installed
2. Open in Dev Container: Open this folder in VS Code and click "Reopen in Container" when prompted
3. Wait for Setup: The container will build and install all dependencies automatically
4. Start Developing: You're ready to build Google ADK applications!
- Python 3.13 - Latest Python version
- VS Code Extensions - Python, Pylint, Black, Jupyter, Google Cloud Code, and more
- Google Cloud SDK - Pre-installed and ready to use
- Git & GitHub CLI - Version control tools
1. Copy .env.example to .env and configure your settings
2. Run adk-setup to authenticate with Google Cloud
3. Set your project ID: gcloud config set project YOUR_PROJECT_ID
This project is set up with a development container optimized for Google Agent Development Kit (ADK) development using Python 3.13.
π Quick Start
1. Prerequisites: Make sure you have VS Code with the Dev Containers extension installed
2. Open in Dev Container: Open this folder in VS Code and click "Reopen in Container" when prompted
3. Wait for Setup: The container will build and install all dependencies automatically
4. Start Developing: You're ready to build Google ADK applications!
π¦ What's Included
Development Environment
- Python 3.13 - Latest Python version - VS Code Extensions - Python, Pylint, Black, Jupyter, Google Cloud Code, and more - Google Cloud SDK - Pre-installed and ready to use - Git & GitHub CLI - Version control toolsPython Packages
- Google Cloud Libraries - Storage, BigQuery, AI Platform, Speech, Vision, etc. - Machine Learning - TensorFlow, PyTorch, Transformers, LangChain - Web Frameworks - FastAPI, Flask, with async support - Development Tools - pytest, ruff, black, mypy, pre-commit - Data Processing - pandas, numpy, matplotlib, plotlyFeatures
- Port Forwarding - Common development ports (3000, 5000, 8000, 8080, 9000) - Custom Aliases - Helpful shortcuts for ADK development - Auto-formatting - Code formatting on save - Testing Setup - pytest configuration - Jupyter Support - For interactive developmentπ§ Configuration
Google Cloud Setup
1. Copy.env.example to .env and configure your settings
2. Run adk-setup to authenticate with Google Cloud
3. Set your project ID: gcloud config set project YOUR_PROJECT_ID
Useful Commands
-adk-setup - Setup Google Cloud authentication
- adk-test - Run tests
- adk-format - Format code with black and fix with ruff
- adk-lint - Run ruff linter
- adk-check - Run full code quality check (ruff + mypy + pytest)
π Project Structure
.devcontainer/
βββ devcontainer.json # Dev container configuration
βββ Dockerfile # Container image definition
βββ bashrc # Custom bash configuration
requirements.txt # Python dependencies
.env.example # Environment variables template
π Development Tips
1. Package Management: This setup uses uv for fast Python package installation
2. Code Quality: Pre-commit hooks are automatically installed with ruff, black, and mypy
3. Authentication: Use gcloud auth application-default login for local development
4. Environment Variables: Copy .env.example to .env and customize
5. Testing: Place tests in a tests/ directory and run with adk-test
6. Linting: Use adk-lint for ruff linting or adk-check for comprehensive checks
π Additional Resources
- Google Agent Development Kit Documentation
- Google Cloud Python Client Libraries
- VS Code Dev Containers
Happy coding! π
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