# Jupyter Notebook

> Use this tool when you need to integrate AI-powered functionality into Jupyter workflows, enabling automated analysis, code generation, and interactive data exploration. It provides a bridge between Model Context Protocol (MCP) and Jupyter environments, allowing AI assistants to execute code and manipulate notebook content. Ideal for data scientists and researchers, it streamlines data analysis and exploration within notebook environments.

Canonical page: https://skillsregistry.net/skills/datalayer-jupyter  
JSON: https://api.skillsregistry.net/v1/skills/datalayer-jupyter

## Description

This Jupyter MCP server implementation, developed by Datalayer, provides a bridge between the Model Context Protocol (MCP) and Jupyter environments. It leverages Jupyter's kernel and notebook model clients to enable AI assistants to interact with Jupyter notebooks, execute code, and manipulate notebook content. The server is designed to run in a Docker container, making it easily deployable and scalable. It's particularly useful for data scientists and researchers who want to integrate AI-powered tools into their Jupyter workflows, enabling automated analysis, code generation, and interactive data exploration within notebook environments.

## Trust

- **Trust score (0–1):** 0.62
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/datalayer-jupyter)
- **Repository:** <https://github.com/datalayer/jupyter-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "datalayer-jupyter"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/datalayer-jupyter` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/datalayer-jupyter/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt