🪐 ✨ Jupyter MCP Server
@MCP-Mirror
关于 🪐 ✨ Jupyter MCP Server
Mirror of
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"datalayer_jupyter-mcp-server": {
"command": "docker",
"args": [
"build",
"-t",
"datalayer/jupyter-mcp-server",
"."
]
}
}
}工具
4`cell_content`(string): Code to be executed
Success message
`cell_content`(string): Markdown content
Success message
概览
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.
数据与分析 分类下的更多 MCP 服务器
MCP Server for Deep Research
reading-plus-aiMCP Server for Data Exploration
reading-plus-ai
Bright Data MCP
luminati-ioA powerful Model Context Protocol (MCP) server that provides an all-in-one solution for public web access.
Google Ads MCP
cohnenAn MCP tool that connects Google Ads with Claude AI/Cursor and others, allowing you to analyze your advertising data through natural language conversations. This integration gives you access to campaign information, performance metrics, keyword analytics, and ad management—all th
Google Analytics MCP Server
surendranbGoogle 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.
评论