jupyter-mcp-serverThis server connects AI assistants directly to your Jupyter Notebooks. It gives you a reliable set of tools to write code, run cells, view charts, and manage multiple notebooks without ever leaving yo

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Reviewed by Daniel Nikulshyn·Updated July 2026

Overview

The Jupyter MCP Server connects AI assistants to Jupyter Notebooks, enabling real-time interaction and management. It allows users to write code, run cells, view charts, and manage multiple notebooks. The server provides tools for interacting with Jupyter notebooks, including server management and multi-notebook management tools. It supports various output types, including images, plots, and text, and is compatible with any Jupyter deployment and MCP client.

Key features

Real-time control
Smart execution
Context-aware interactions
Multimodal support
Multi-notebook support
JupyterLab integration

Pricing

Model: Free
Category: MCP Servers
Rating: No reviews yet

Use cases

AI-assisted Jupyter Notebook development

The Jupyter MCP Server enables AI assistants to connect to Jupyter Notebooks, allowing for real-time code writing, cell execution, and chart viewing.

Multi-notebook management

The server supports seamless switching between multiple notebooks, making it easier to manage and interact with multiple notebooks.

Pros & Cons

Pros

Real-time control and instant notebook change updates
Smart execution with automatic adjustment on cell run failure
Context-aware interactions with the entire notebook context
Multimodal support for different output types
Seamless multi-notebook support and switching

Cons

Configuration required for MCP_TOKEN in MCP client setup
Limited information on compatibility with specific JupyterHub and Google Colab deployments

Reviews

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Q&A

Can the server handle multiple notebooks at once and switch between them?

Yes, it includes multi‑notebook support that lets you manage and switch between several notebooks in real time, preserving context and allowing seamless execution across them.

Asked by Lorenzo Bianchi · Sep 14, 2025

What setup is required for the MCP client to communicate with the server?

You must configure an MCP_TOKEN in the MCP client settings so the client can authenticate with the server. Once the token is set, the client can control notebooks, run cells, and retrieve outputs.

Asked by Lindiwe Mahlangu · Sep 7, 2025

How does the Jupyter MCP Server integrate with my existing JupyterLab environment?

The server plugs directly into JupyterLab, offering UI enhancements like automatic notebook opening and real‑time updates. It works with any standard Jupyter deployment, including local JupyterLab, JupyterHub, and Datalayer‑hosted notebooks.

Asked by Joanna Kowalski · Aug 22, 2025