# JupyterMCP

> Use this tool when you need to programmatically control Jupyter notebooks remotely, enabling AI assistants and applications to create, edit, and execute notebook cells. It solves problems of automated notebook management and integration with external systems, providing an interface for sending and receiving cell updates via SSE protocol. Ideal for use cases requiring dynamic notebook interaction, such as automated data analysis and machine learning workflows.

Canonical page: https://skillsregistry.net/skills/ilylty-jupytermcp  
JSON: https://api.skillsregistry.net/v1/skills/ilylty-jupytermcp

## Description

A Model Control Protocol (MCP) server that enables remote programmatic control of Jupyter notebooks, allowing AI assistants and applications to create, edit, and execute notebook cells via SSE protocol.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bpfyspx1p9)
- **Repository:** <https://github.com/ilylty/jupyterMCP>

## 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": "ilylty-jupytermcp"
    }
  }
}
```

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