Jupyter MCP Server

@datalayer

代码仓库主页

基本信息

分类

数据与分析

许可证

BSD-3-Clause

传输方式

stdio

作者

datalayer

关于 Jupyter MCP Server

🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.

#tools #ai #jupyter #mcp #mcp-server

Jupyter MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

Jupyter MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🪐✨ Jupyter MCP Server?

An open-source MCP server that enables AI agents to connect to and manage Jupyter Notebooks in real-time. It bridges AI assistants with Jupyter environments, allowing direct notebook creation, cell execution, and output retrieval. Developed by Datalayer.

How to use 🪐✨ Jupyter MCP Server?

Install via pip install jupyter-mcp-server and configure your MCP client with environment variables JUPYTER_URL, JUPYTER_TOKEN, and ALLOW_IMG_OUTPUT. Run using uvx for quick start or Docker for production. Alternatively, run as a Jupyter Server extension. The server supports STDIO and Streamable HTTP transports.

Key features of 🪐✨ Jupyter MCP Server

Real-time notebook control with instant output viewing.
Smart execution that adjusts after cell failures.
Context-aware understanding of entire notebooks.
Multimodal output support (images, plots, text).
Multi-notebook switching and management.
JupyterLab integration with additional commands.

Use cases of 🪐✨ Jupyter MCP Server

AI-assisted code development and debugging in Jupyter.
Automated data analysis and visualization workflows.
Interactive exploration of notebooks via natural language.
Orchestrating multi-notebook experiments with an AI agent.
Real-time collaborative editing with JupyterLab integration.

常见问题

What MCP clients are supported?

Works with any MCP client, including Claude Desktop, Cursor, Windsurf, and others.

How do I configure the server?

Set `JUPYTER_URL`, `JUPYTER_TOKEN`, and `ALLOW_IMG_OUTPUT` environment variables. A `MCP_TOKEN` is also required since version 1.0.0.

Is Docker supported?

Yes. Use the `datalayer/jupyter-mcp-server` Docker image with environment variables passed at runtime.

What are the runtime requirements?

Python environment with JupyterLab 4.4.1+, `jupyter-collaboration`, `jupyter-mcp-tools`, `ipykernel`, and `pycrdt`. Starting v1.0.2, `datalayer_pycrdt` is no longer needed.

Does it support JupyterHub or Google Colab?

Support for JupyterHub and Google Colab deployments is actively being developed; user feedback is welcome.

数据与分析分类下的更多 MCP 服务器

Instagram MCP Server

HasData

Read public Instagram profiles and post feeds by handle in Claude, Cursor, and other MCP clients. Get follower counts, captions, hashtags, mentions, and engagement counts as structured JSON.

CoinLobster

The only MCP server with live whale trades across 15 exchanges plus on-chain DEX flow. Smart Money Radar, real liquidations and outcome-scored signals. No API key required.

AskRentAI

Ask your Rent Manager property portfolio anything, from the AI you already use. AskRentAI is a hosted, read-only MCP server for Rent Manager, the property management platform used across a large share of US rental housi

Lawstronaut Legal Research

Lawstronaut-FZCO

Connect your AI to millions of laws and court cases! Lawstronaut is the infrastructure layer that connects AI agents and software to millions of legal documents across 150+ jurisdictions, structured legal data, continuou

hedwigai

Research workbooks your agent keeps current: spreadsheets and memos where every figure cites its primary source (SEC filings, customs records, trial registries), plus data programs such as website traffic for 1,000 domai