Datalayer Provider

The Jupyter MCP Server can execute code on the Datalayer cloud code sandbox, providing fully isolated execution with GPU support, snapshots, and persistence. Execution is routed through the code-sandboxes datalayer engine, which is powered by agent_code_sandboxes.

tip

For the full, engine-level credential and parameter reference, see the Datalayer sandbox guide in the code-sandboxes documentation.

Requirements

Install the Datalayer extra:

pip install "jupyter-mcp-server[datalayer]"

Install the sandbox extension package used by this provider:

pip install datalayer_mcp_sandboxes

Credentials

1. Create an account at datalayer.ai.
2. Generate an API token from your account settings (IAM → Tokens / API Keys).
3. Export it as an environment variable:

Environment variable	Description
DATALAYER_API_KEY	API key for Datalayer code sandbox authentication
DATALAYER_RUN_URL	Custom Datalayer service URL (optional, self-hosted)

Configuration

Select the Datalayer engine with SANDBOX_VARIANT=datalayer:

SANDBOX_VARIANT=datalayer
DATALAYER_API_KEY=your-datalayer-token

MCP client configuration:

{
  "mcpServers": {
    "jupyter": {
      "command": "uvx",
      "args": ["jupyter-mcp-server@latest"],
      "env": {
        "SANDBOX_VARIANT": "datalayer",
        "DATALAYER_API_KEY": "your-datalayer-token"
      }
    }
  }
}