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# 🪐✨ Jupyter MCP Server
[](https://pypi.org/project/jupyter-mcp-server)
<a href="https://mseep.ai/app/datalayer-jupyter-mcp-server">
<img src="https://mseep.net/pr/datalayer-jupyter-mcp-server-badge.png" alt="MseeP.ai Security Assessment Badge" width="100" />
</a>
[](https://archestra.ai/mcp-catalog/datalayer__jupyter-mcp-server)
> 🚨 **BREAKING CHANGE** For version `0.11.0+`, `room` has been renamed to `document`. [Read more in the release notes.](https://jupyter-mcp-server.datalayer.tech/releases)
**Jupyter MCP Server** is a [Model Context Protocol](https://modelcontextprotocol.io) (MCP) server implementation that enables **real-time** interaction with 📓 Jupyter Notebooks, allowing AI to edit, document and execute code for data analysis, visualization etc.
Compatible with any Jupyter deployment (local, JupyterHub, ...) and with [Datalayer](https://datalayer.ai/) hosted Notebooks.
## 🚀 Key Features
- ⚡ **Real-time control:** Instantly view notebook changes as they happen.
- 🔁 **Smart execution:** Automatically adjusts when a cell run fails thanks to cell output feedback.
- 🤝 **MCP-Compatible:** Works with any MCP client, such as Claude Desktop, Cursor, Windsurf, and more.
🛠️ This MCP offers multiple tools such as `insert_execute_code_cell`, `append_markdown_cell`, `get_notebook_info`, `read_cell`, and more, enabling advanced interactions with Jupyter notebooks. Explore our [tools documentation](https://jupyter-mcp-server.datalayer.tech/tools) to learn about all the tools powering Jupyter MCP Server.
## 🏁 Getting Started
For comprehensive setup instructions—including `Streamable HTTP` transport and advanced configuration—check out [our documentation](https://jupyter-mcp-server.datalayer.tech/). Or, get started quickly with `JupyterLab` and `stdio` transport here below.
### 1. Set Up Your Environment
```bash
pip install jupyterlab==4.4.1 jupyter-collaboration==4.0.2 ipykernel
pip uninstall -y pycrdt datalayer_pycrdt
pip install datalayer_pycrdt==0.12.17
```
### 2. Start JupyterLab
```bash
# make jupyterlab
jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0
```
### 3. Configure Your Preferred MCP Client
> [!NOTE]
>
> Ensure the `port` of the `DOCUMENT_URL` and `RUNTIME_URL` match those used in the `jupyter lab` command.
>
> The `DOCUMENT_ID` which is the path to the notebook you want to connect to, should be relative to the directory where JupyterLab was started.
>
> In a basic setup, `DOCUMENT_URL` and `RUNTIME_URL` are the same. `DOCUMENT_TOKEN`, and `RUNTIME_TOKEN` are also the same and is actually the Jupyter Token.
#### MacOS and Windows
```json
{
"mcpServers": {
"jupyter": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DOCUMENT_URL",
"-e",
"DOCUMENT_TOKEN",
"-e",
"DOCUMENT_ID",
"-e",
"RUNTIME_URL",
"-e",
"RUNTIME_TOKEN",
"datalayer/jupyter-mcp-server:latest"
],
"env": {
"DOCUMENT_URL": "http://host.docker.internal:8888",
"DOCUMENT_TOKEN": "MY_TOKEN",
"DOCUMENT_ID": "notebook.ipynb",
"RUNTIME_URL": "http://host.docker.internal:8888",
"RUNTIME_TOKEN": "MY_TOKEN"
}
}
}
}
```
#### Linux
```json
{
"mcpServers": {
"jupyter": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DOCUMENT_URL",
"-e",
"DOCUMENT_TOKEN",
"-e",
"DOCUMENT_ID",
"-e",
"RUNTIME_URL",
"-e",
"RUNTIME_TOKEN",
"--network=host",
"datalayer/jupyter-mcp-server:latest"
],
"env": {
"DOCUMENT_URL": "http://localhost:8888",
"DOCUMENT_TOKEN": "MY_TOKEN",
"DOCUMENT_ID": "notebook.ipynb",
"RUNTIME_URL": "http://localhost:8888",
"RUNTIME_TOKEN": "MY_TOKEN"
}
}
}
}
```
For detailed instructions on configuring various MCP clients—including [Claude Desktop](https://jupyter-mcp-server.datalayer.tech/clients/claude_desktop), [VS Code](https://jupyter-mcp-server.datalayer.tech/clients/vscode), [Cursor](https://jupyter-mcp-server.datalayer.tech/clients/cursor), [Cline](https://jupyter-mcp-server.datalayer.tech/clients/cline), and [Windsurf](https://jupyter-mcp-server.datalayer.tech/clients/windsurf) — see the [Clients documentation](https://jupyter-mcp-server.datalayer.tech/clients).
## 📚 Resources
Looking for blog posts, videos, or other materials about Jupyter MCP Server?
👉 Visit the [Resources section](https://jupyter-mcp-server.datalayer.tech/resources).