Using Agent Sandbox as a Tool in Agent Development Kit (ADK)

The guide walks you through the process of creating a simple ADK agent that is able to use agent sandbox as a tool.

Installation

1. Install the Agent-Sandbox controller and CRDs to a cluster. You can follow the instructions from the installation section from the Getting Started page.

2. Install the Agent Sandbox router

3. Create a Python virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate
   

4. Install the dependencies:

   export VERSION="main"
   pip install google-adk==1.19.0 "git+https://github.com/kubernetes-sigs/agent-sandbox.git@${VERSION}#subdirectory=clients/python/agentic-sandbox-client"
   

5. Create a new ADK project:

   adk create coding_agent
   

6. Replace the content of the coding_agent/agent.py file with the following:

   from google.adk.agents.llm_agent import Agent
   from agentic_sandbox import SandboxClient
   
   
   def execute_python(code: str):
       with SandboxClient(
           template_name="python-sandbox-template",
           namespace="default"
       ) as sandbox:
           sandbox.write("run.py", code)
           result = sandbox.run("python3 run.py")
           return result.stdout
   
   
   root_agent = Agent(
       model='gemini-2.5-flash',
       name='coding_agent',
       description="Writes Python code and executes it in a sandbox.",
       instruction="You are a helpful assistant that can write Python code and execute it in the sandbox. Use the 'execute_python' tool for this purpose.",
       tools=[execute_python],
   )
   

   As you can see, the Agent Sandbox is called by a wrapper function execute_python which, in turn, is used by the Agent class as a tool.

7. Run the agent in ADK’s built in server:

   adk web
   

Testing

1. Open the agent’s page: http://127.0.0.1:8000.

2. Tell the agent to generate some code and execute it in the sandbox:

The agent should generate the code and execute it in the agent-sandbox.