How do I install the jupyter mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

What credentials does it need?

It reads `JUPYTER_URL`, `JUPYTER_TOKEN`, `ALLOW_IMG_OUTPUT`, `CODE_SANDBOX_URL`, `CODE_SANDBOX_TOKEN`, `DOCUMENT_URL`, `DOCUMENT_TOKEN`, `SANDBOX_VARIANT` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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Jupyter MCP Server

Compatible with any Jupyter deployment (local, JupyterHub, ...) and with [Datalayer](https://datalayer.ai) hosted Notebooks.

Remote serverstreamable-httpPython

What is the Jupyter MCP Server?

Jupyter becomes available to MCP clients through the jupyter mcp server. Compatible with any Jupyter deployment (local, JupyterHub, ...) and with Datalayer hosted Notebooks.

What Jupyter does

Compatible with any Jupyter deployment (local, JupyterHub, ...) and with Datalayer hosted Notebooks.

Practical notes

Maintained by datalayer, written in Python.

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

Tool	What it does
list_files	List files and directories in the Jupyter server's file system.
list_kernels	List all available and running kernel sessions on the Jupyter server.
launch_sandbox	Launch a code sandbox (eval/docker/jupyter/datalayer/kaggle/colab/monty/modal) as an alternative execution backend for execute_code. Supports variant-specific options including GPU flavor for supported backends. Requires
list_sandboxes	List launched code sandboxes and their state (active flag, variant, status, and selected code sandbox options). Requires the jupyter_mcp_sandboxes extension.
use_sandbox	Select or clear the active sandbox used by execute_code, enabling dynamic routing between kernel-backed and sandbox-backed execution. Requires the jupyter_mcp_sandboxes extension.
terminate_sandbox	Stop and unregister a launched code sandbox. Requires the jupyter_mcp_sandboxes extension.
connect_to_jupyter	Connect to a Jupyter server dynamically without restarting the MCP server. Not available when running as Jupyter extension. Useful for switching servers dynamically or avoiding hardcoded configuration. [Read more](http
use_notebook	Connect to a notebook file, create a new one, or switch between notebooks.
list_notebooks	List all notebooks available on the Jupyter server and their status
restart_notebook	Restart the kernel for a specific managed notebook.
unuse_notebook	Disconnect from a specific notebook and release its resources.
read_notebook	Read notebook cells source content with brief or detailed format options.
read_cell	Read the full content (Metadata, Source and Outputs) of a single cell.
insert_cell	Insert a new code or markdown cell at a specified position.

How to install the Jupyter MCP Server

{
  "mcpServers": {
    "jupyter": {
      "command": "uvx",
      "args": [
        "jupyter-mcp-server@latest"
      ],
      "env": {
        "JUPYTER_URL": "http://localhost:8888",
        "JUPYTER_TOKEN": "YOUR_JUPYTER_TOKEN",
        "ALLOW_IMG_OUTPUT": "true"
      }
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

Variable	Description	Required
JUPYTER_URL	Declared in the maintainer’s client configuration.	Check documentation
JUPYTER_TOKEN	Declared in the maintainer’s client configuration.	Check documentation
ALLOW_IMG_OUTPUT	Declared in the maintainer’s client configuration.	Check documentation

Example prompts to try

“Use Jupyter to list files.”
“Use Jupyter to list kernels.”
“Use Jupyter to launch sandbox.”

Frequently asked questions

Compatible with any Jupyter deployment (local, JupyterHub, ...) and with [Datalayer](https://datalayer.ai) hosted Notebooks. Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.