This Jupyter MCP server implementation, developed by Datalayer, provides a bridge between the Model Context Protocol (MCP) and Jupyter environments. It leverages Jupyter's kernel and notebook model clients to enable AI assistants to interact with Jupyter notebooks, execute code, and manipulate notebook content. The server is designed to run in a Docker container, making it easily deployable and scalable. It's particularly useful for data scientists and researchers who want to integrate AI-powered tools into their Jupyter workflows, enabling automated analysis, code generation, and interactive data exploration within notebook environments.
Add and execute a code cell in a Jupyter notebook. Input: cell_content (string): Code to be executed. Returns: Cell output.
Add a markdown cell in a Jupyter notebook. Input: cell_content (string): Markdown content. Returns: Success message.
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