Build and Deploy Java AI Agents with Google ADK

A developer built and deployed a Java AI agent using the Google Agent Development Kit (ADK) on Debian 13. The agent, which provides time and weather information, was compiled with Java 25 and deployed to Google Cloud Run. The complete project is available in a sample repository.

Debian 13 “Trixie” provides a clean, stable base for Java agent development. On a workstation, virtual machine, or cloud instance, you can compile Java projects, run local web servers, use the Google Agent Development Kit ADK Dev UI, and deploy an agent to Google Cloud Run. This guide builds a small ADK agent with time and weather tools. The complete project is available in the sample repository https://github.com/xbill9/adk-hello-world-java . Start with a Debian 13 installation and a user account that can run sudo . Confirm the operating-system version: . /etc/os-release printf '%s %s %s \n' "$NAME" "$VERSION ID" "$VERSION CODENAME" Update the package index and install the base development tools: sudo apt-get update sudo apt-get install -y curl git maven unzip zip This project compiles with Java 25. One convenient way to install a matching JDK is SDKMAN https://sdkman.io/install/ : curl -s "https://get.sdkman.io" | bash source "$HOME/.sdkman/bin/sdkman-init.sh" sdk list java Select an available Java 25 identifier from the list and install it for example, 25-open : sdk install java 25-open java --version mvn --version Both commands should report Java 25, and Maven must be version 3.6.3 or newer. The build enforces this minimum Maven version. Add Google's Debian package repository: sudo apt-get install -y apt-transport-https ca-certificates gnupg curl https://packages.cloud.google.com/apt/doc/apt-key.gpg \ | sudo gpg --dearmor -o /usr/share/keyrings/cloud.google.gpg echo "deb signed-by=/usr/share/keyrings/cloud.google.gpg https://packages.cloud.google.com/apt cloud-sdk main" \ | sudo tee /etc/apt/sources.list.d/google-cloud-sdk.list sudo apt-get update sudo apt-get install -y google-cloud-cli Verify the installation: gcloud version The Google Cloud CLI is required for Vertex AI authentication and Cloud Run deployment. It is not required if you only run the agent locally with a Gemini API key. git clone https://github.com/xbill9/adk-hello-world-java cd adk-hello-world-java The agent lives at src/main/java/agents/multitool/MultiToolAgent.java . Its public ROOT AGENT field lets the ADK Dev UI discover it: public static final BaseAgent ROOT AGENT = initAgent ; public static BaseAgent initAgent { return LlmAgent.builder .name "multi tool agent" .model "gemini-2.5-flash" .description "Agent to answer questions about the time and weather in a city." .tools FunctionTool.create MultiToolAgent.class, "getCurrentTime" , FunctionTool.create MultiToolAgent.class, "getWeather" .build ; } The tools return structured maps with a status and a human-readable report . The time tool uses IANA time zones and includes aliases for cities such as San Francisco, Beijing, and Mumbai. This sample uses ADK for Java 1.7.0 , the latest release available from Maven Central as of July 27, 2026. Both runtime dependencies use the same property so the core library and Dev UI cannot drift to different versions: <properties <google-adk.version 1.7.0</google-adk.version </properties <dependency <groupId com.google.adk</groupId <artifactId google-adk</artifactId <version ${google-adk.version}</version </dependency <dependency <groupId com.google.adk</groupId <artifactId google-adk-dev</artifactId <version ${google-adk.version}</version </dependency Recent changes relevant to this project include: VertexAiSessionService . gen ai.usage.input tokens . gemini-2.5-flash for a stable, broadly available tutorial baseline.These are framework improvements; the sample does not reimplement them. Keeping the ADK dependencies pinned to 1.7.0 is what brings them into the application. Run the setup script: ./init.sh It offers two modes: ~/gemini.key with user-only permissions.The selected mode is stored in ~/.adk-hello-world-java-auth . Run ./init.sh again whenever you want to switch modes. The launch scripts source set env.sh automatically, so you do not need to export the variables by hand. For Vertex AI, your account and the Cloud Run service identity must have the required Vertex AI permissions. Cloud Run uses its service identity at runtime rather than a downloaded credential file. Compile the project and run its eight JUnit Jupiter tests: make build make test The tests cover agent initialization, supported and unsupported cities, time-zone aliases, and null input. Run Checkstyle separately: make lint The lint target fails when Google Java Style warnings are found, which makes it useful in local development and continuous integration. ./cli.sh Example session: You What is the current time in Tokyo? Agent The current time in Tokyo is 08:24. You What is the weather in New York? Agent The weather in New York is sunny with a temperature of 25 degrees Celsius 77 degrees Fahrenheit . You quit Start the local server: ./devui.sh Open http://127.0.0.1:8080 http://127.0.0.1:8080 in your browser. ADK scans the Maven output under target/classes and makes multi tool agent available in the UI. The web.sh script is retained as an alias for devui.sh . ADK 1.6 tightened WebSocket origin handling and warns when the Dev UI uses the CORS default. That default is convenient for local development but should not be treated as an access-control mechanism for a public deployment. Cloud Run deployment uses Vertex AI rather than copying a local API key into the service. If you selected API-key mode, run ./init.sh again and choose Vertex AI. Then deploy: ./cloudrun.sh The script runs one source deployment for the adk-hello-world-java service in us-central1 . Because the repository contains a Dockerfile, Cloud Run builds that Dockerfile remotely; Docker does not need to be installed on the Debian system. The container reads Cloud Run's PORT environment variable and starts the ADK web server. When deployment completes, gcloud prints the service URL. The deployment is private by default because the service includes the ADK Dev UI and API. Configure authenticated callers with Cloud Run IAM. For a disposable public demonstration, replace --no-allow-unauthenticated with --allow-unauthenticated in cloudrun.sh ; do not rely on CORS as access control. . ├── .dockerignore ├── .gcloudignore ├── Dockerfile ├── Makefile ├── cli.sh ├── cloudrun.sh ├── devui.sh ├── init.sh ├── pom.xml ├── set env.sh └── src ├── main/java/agents/multitool/MultiToolAgent.java └── test/java/agents/multitool/MultiToolAgentTest.java Debian Trixie provides everything needed to build and test a Java ADK agent locally. This sample keeps local authentication explicit, verifies the tool logic with JUnit, enforces Java style with Checkstyle, and uses Vertex AI service identity when deployed to Cloud Run.