MCP.so
Sign In

🪐 ✨ Jupyter MCP Server

@MCP-Mirror

Repository

About 🪐 ✨ Jupyter MCP Server

Mirror of

#jupyter#mcp-server#data-science

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "datalayer_jupyter-mcp-server": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "datalayer/jupyter-mcp-server",
        "."
      ]
    }
  }
}

Tools

4

`cell_content`(string): Code to be executed

Success message

`cell_content`(string): Markdown content

Success message

Overview

What is Jupyter MCP Server?

Jupyter MCP Server is a Model Context Protocol (MCP) server that enables interaction with Jupyter notebooks running in a local JupyterLab instance. Designed for AI agents and developers, it uses Jupyter Real Time Collaboration (RTC) to reflect notebook modifications live.

How to use Jupyter MCP Server?

Start JupyterLab with token authentication (jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0) and install the required packages (jupyterlab, jupyter-collaboration, ipykernel). Then configure the MCP client (e.g., Claude Desktop) to run the Docker image datalayer/jupyter-mcp-server:latest, setting environment variables SERVER_URL, TOKEN, and NOTEBOOK_PATH to match your JupyterLab session.

Key features of Jupyter MCP Server

  • Connect AI agents to live Jupyter notebooks
  • Add and execute code cells remotely
  • Insert Markdown cells into notebooks
  • Uses Docker for easy deployment
  • Works with JupyterLab’s Real Time Collaboration

Use cases of Jupyter MCP Server

  • Enable a language model to run Python code in a Jupyter notebook
  • Automatically generate and insert analysis cells with results
  • Combine AI-generated explanations with computed outputs in a single notebook

FAQ from Jupyter MCP Server

What tools does Jupyter MCP Server offer?

Two tools: add_execute_code_cell (executes Python code and returns success) and add_markdown_cell (adds Markdown content). Both take a cell_content string.

What are the runtime dependencies?

A local JupyterLab with jupyter-collaboration and ipykernel installed, plus Docker to run the MCP server container.

How do I authenticate to my JupyterLab instance?

You must set a token via --IdentityProvider.token MY_TOKEN when starting JupyterLab, then provide the same token in the TOKEN environment variable in the MCP client configuration.

How does the server connect to a running JupyterLab?

The SERVER_URL environment variable (e.g., http://localhost:8888) tells the Docker container where JupyterLab is listening. On Linux, the --network=host Docker flag is used; on macOS/Windows, the container accesses the host via host.docker.internal.

Can I install Jupyter MCP Server without Docker?

The README only shows distribution via Docker or Smithery. There is no pip-based installation described.

Frequently asked questions

What tools does Jupyter MCP Server offer?

Two tools: `add_execute_code_cell` (executes Python code and returns success) and `add_markdown_cell` (adds Markdown content). Both take a `cell_content` string.

What are the runtime dependencies?

A local JupyterLab with `jupyter-collaboration` and `ipykernel` installed, plus Docker to run the MCP server container.

How do I authenticate to my JupyterLab instance?

You must set a token via `--IdentityProvider.token MY_TOKEN` when starting JupyterLab, then provide the same token in the `TOKEN` environment variable in the MCP client configuration.

How does the server connect to a running JupyterLab?

The `SERVER_URL` environment variable (e.g., `http://localhost:8888`) tells the Docker container where JupyterLab is listening. On Linux, the `--network=host` Docker flag is used; on macOS/Windows, the container accesses the host via `host.docker.internal`.

Can I install Jupyter MCP Server without Docker?

The README only shows distribution via Docker or Smithery. There is no pip-based installation described.

Comments

Basic information

Category

Data & Analytics

Transports

stdio

Author

MCP-Mirror

More Data & Analytics MCP servers

Sugra API MCP

Sugra Systems, Inc.

Official MCP server for the Sugra API, giving AI agents source-attributed access to 1,500+ endpoints across 36 data domains from 160+ primary sources. Covers markets, economics, company fundamentals, government, news, cl

1

Google Analytics MCP Server

surendranb

Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side aggregation, and safe defaults that reduce data wrangling.

225

MCP.science: Open Source MCP Servers for Scientific Research 🔍📚

pathintegral-institute

Open Source MCP Servers for Scientific Research

142

Opinly

Track competitors, rankings, and how AI answers rank you — then write and publish the fix.

Octolens

Octolens

Give your AI agents every brand mention across the internet — 15+ platforms, AI-filtered, one structured feed.