CoreWeave Serverless sandboxes are in public preview.
managed-agents-2026-04-01 beta header. The Anthropic SDK used in this guide adds it automatically. See Anthropic beta access.
Prerequisites
Before you begin, you need the following:- A W&B API key. These examples use W&B authentication. For other credentials, see Choose a credential.
- Claude Managed Agents access in your Anthropic workspace and a Console API key for the client that creates sessions.
- An existing agent configured with
agent_toolset_20260401. Follow Anthropic’s Managed Agents quick start to create one and record its ID. - For the SDK examples, either Python 3.11 or later with
uv, or Node.js 22 or later.
cws-agent selects W&B authentication:
SANDBOX_USER Identity and Access Management (IAM) action. That permission applies only when authenticating with a CoreWeave API access token.
Create an environment
In the Claude Console, create a Self-hosted environment. Open it and generate an environment key. Record the environment ID and store the key securely. See Anthropic’s environment setup. The environment key authenticates workers to this environment. The Console API key creates sessions from your client. Keep the two credentials separate. For the verification task, use an environment with only the worker created in this guide. That prevents another worker from claiming the test session. With the environment ready, choose eithercws-agent or the Sandbox SDK to start its worker, then run the verification task.
Quick start with cws-agent
Follow thecws-agent installation instructions. The tool configures a snapshot volume to save and restore your workspace with file system snapshots.
Replace [ENVIRONMENT-KEY], [ENVIRONMENT-ID], and [SANDBOX-NAME] with your environment key, environment ID, and a cws-agent session name for the sandbox. For the session name, use 1 to 40 lowercase letters, digits, or hyphens, starting with a letter or digit:
/workspace/claude/0 and returns to your shell. The tool passes the environment key into the sandbox. For platform-managed secret references, see Use a secret store.
To view the worker’s terminal, run:
cws-agent run command doesn’t drive Managed Agents conversations.
Set up with the Sandbox SDK
This alternative starts Anthropic’sant worker as the sandbox’s main process. It doesn’t require cws-agent or configure snapshots.
Run Python snippets in the virtual environment created in this guide. Save TypeScript snippets as .mts files in the project where you install the client, then run them with npx tsx [FILENAME].mts.
Configure credentials and install the client
Export the environment key and ID from the Console in the terminal where you run the script:- Python
- TypeScript
Use Python 3.11 or later and
uv:Start the worker
Save the script for your language using the filename shown. The script installs theant CLI in a Linux image with Bash, starts one worker, and prints the sandbox ID. The client reads ANTHROPIC_ENVIRONMENT_KEY from your local environment and passes its value in the sandbox request to set the worker’s environment variable.
- Python
- TypeScript
start_claude_worker.py
- Python
- TypeScript
wait() can also return if the main process has already completed. A printed sandbox ID doesn’t confirm that the worker is authenticated or polling. Before starting a task, inspect its status and recent logs. Replace [SANDBOX-ID] with the printed ID:
- Python
- TypeScript
Optional: Use a secret store
If your administrator has configured a secret store for your organization, you can pass a reference instead of the environment key value. Store the key there and obtain the verified store and entry names from your administrator. There is no universal store name.- Python
- TypeScript
Import
Secret from cwsandbox, remove ANTHROPIC_ENVIRONMENT_KEY from environment_variables, and add secrets=[Secret(store="[SECRET-STORE]", name="[SECRET-NAME]", env_var="ANTHROPIC_ENVIRONMENT_KEY")] to Sandbox.run().Run and verify a task
Run the session client on your own machine for either setup path. Install the Anthropic SDK for your language:- Python
- TypeScript
[ANTHROPIC-API-KEY] with your Console API key, [AGENT-ID] with your existing agent ID, and [ENVIRONMENT-ID] with the environment connected to your worker:
- Python
- TypeScript
verify_claude_worker.py
- Python
- TypeScript
requires_action, inspect the referenced tool events. Calls with evaluated_permission: "ask" need Anthropic’s tool-confirmation workflow. The worker handles allowed calls. If they stall, inspect its logs. Keep the session ID to continue that session rather than creating another one.
After the task completes, read the file from the sandbox with the command for your setup. Replace [SANDBOX-NAME] or [SANDBOX-ID] with the workspace name or printed sandbox ID:
- cws-agent
- Sandbox SDK
cwsandbox if needed. For TypeScript, save the SDK snippet as an .mts file and run it with npx tsx.
The file must match the value printed by the client. This ties the agent’s tool execution to the specific CoreWeave sandbox.
Keep results and stop
Wait for active tasks to finish and copy any results you need out of the sandbox. Then stop it using the command for your setup:- cws-agent
- Sandbox SDK
down snapshots the workspace before stopping. If capture fails, check cws-agent status [SANDBOX-NAME] and resolve the failure before retrying. If you can discard unsaved changes, use down --no-snapshot.Troubleshoot
Use these checks to resolve common issues:- If the session waits for a worker, check the environment ID, the worker logs, and whether another task already occupies the worker.
- If the worker can’t authenticate, check its environment key. The Console API key used by the session client is a different credential.
- If a tool is missing, build an image with the required dependencies. The example uses a Python image and doesn’t install a project-specific toolchain.