What limitation does this server address?
As of Cursor version 0.50.5, the agent mode could not edit Jupyter Notebook cells. This server provides MCP tools that enable direct cell manipulation.
@jbeno
基本信息
Model Context Protocol (MCP) server designed to allow AI agents within Cursor to interact with Jupyter Notebook (.ipynb) files
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"cursor-notebook-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"cursor-notebook-mcp"
]
}
}
}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。
Jupyter Notebook MCP Server (for Cursor) is a Model Context Protocol server that allows AI agents within Cursor to interact directly with Jupyter Notebook (.ipynb) files. It overcomes Cursor’s limitation (as of version 0.50.5) where the agent mode could not edit notebooks or cells. The server uses nbformat for safe notebook manipulation and nbconvert for exporting, and restricts operations to user-defined directories for security.
Install with pip install cursor-notebook-mcp (Python 3.10+). Then start the server manually: cursor-notebook-mcp --transport streamable-http --allow-root /path/to/notebooks --host 127.0.0.1 --port 8080. Configure Cursor by adding a "notebook_mcp" entry to ~/.cursor/mcp.json with the server URL (http://127.0.0.1:8080/mcp).
As of Cursor version 0.50.5, the agent mode could not edit Jupyter Notebook cells. This server provides MCP tools that enable direct cell manipulation.
Yes. Although designed for Cursor, it has no Cursor‑specific code beyond configuration instructions. It can be configured for VS Code (Insiders), Claude Code, or any MCP‑compatible agent.
Python 3.10+ is required. All Python dependencies are installed automatically with the package. Optional external dependencies Pandoc and LaTeX are needed for certain nbconvert export formats (e.g., PDF).
The server restricts all file operations to directories specified via the `--allow-root` flag. This prevents the AI agent from accessing files outside the permitted paths.
The server supports stdio, Streamable HTTP (recommended), and SSE (legacy) transports. Configuration for Cursor is provided for Streamable HTTP and SSE.
The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs
Project context your AI can query through MCP — with source evidence.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age
评论