# JupyterMCP

> Use this tool when you need to interact with Jupyter notebooks programmatically, enabling automation of data science workflows and integration with AI systems. It solves problems such as automating notebook execution, managing remote Jupyter servers, and streamlining kernel management. With inputs including notebook files and kernel connections, and outputs including executed code results and notebook edits, JupyterMCP provides a flexible interface for AI agents to leverage Jupyter's capabilities.

Canonical page: https://skillsregistry.net/skills/try3d-jupytermcp  
JSON: https://api.skillsregistry.net/v1/skills/try3d-jupytermcp

## Description

Enables AI agents to create, read, edit, and execute Jupyter notebook cells, manage kernels, and connect to remote Jupyter servers.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pcolzyxr32)
- **Repository:** <https://github.com/Try3D/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": "try3d-jupytermcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/try3d-jupytermcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/try3d-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