The Jupyter MCP Server is a service that implements the Model Context Protocol (MCP) and supports interaction with Jupyter notebooks.

Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework designed for JupyterLab. It supports models from GitHub Copilot and other LLM providers, including local Ollama models. It significantly enhances productivity through features such as code generation, auto - completion, and chat interfaces, and supports the integration of Model Context Protocol (MCP) services.

This project implements functions similar to Claude Code through the MCP protocol, providing tools for code understanding, modification, and command execution. It supports multiple models and Jupyter notebook operations, and has security control and development expansion capabilities.

JupyterMCP is a tool that integrates Jupyter Notebook with Claude AI via the Model Context Protocol (MCP). It supports functions such as bidirectional communication, cell operations, and code execution, and is only compatible with Jupyter Notebook version 6.x.

The Databricks MCP Server is a service based on the MCP protocol that allows LLM tools to interact with the Databricks platform, providing management functions for clusters, jobs, notebooks, etc.

A security-enhanced version of the NotebookLM MCP server that provides zero-hallucination answers, Gemini in-depth research, document API, and programmatic notebook creation functions, with 14 layers of enterprise-level security protection, including post-quantum encryption, certificate pinning, and compliance support.

This project is a Kaggle MCP server built on the FastMCP library, which provides functions for searching and downloading Kaggle datasets and can generate EDA notebook prompts.

An MCP server that enables interaction with the OneNote web version through browser automation, supporting AI assistants to programmatically operate shared notebooks.

The Databricks MCP Server is a model interaction service based on the MCP protocol, providing access interfaces to functions such as Databricks clusters, jobs, and notebooks, and supporting the integrated interaction between LLM tools and the Databricks platform.

This is a server based on the Model Context Protocol that provides tools for interacting with the Open Notebook API, supporting functions such as managing notebooks, content sources, notes, searches, and AI conversations.

The Sandbox Fusion MCP Server is an implementation that provides code interpreter functionality for large language models. It supports code execution in multiple programming languages and Jupyter notebook operations, and communicates with clients through stdio interaction.

NotebookLM MCP is a professional Google NotebookLM automated MCP server that provides fast, type-safe tool integration, supporting multiple transport protocols and persistent authentication management.

A Model Context Protocol (MCP) server implemented for Microsoft OneNote, providing a standardized interface for AI language models to interact with OneNote and supporting management functions for notebooks, sections, and pages.

The Jupyter Earth MCP Server is a service implementation based on the Model Context Protocol (MCP), providing tool support for geospatial analysis in Jupyter notebooks.

An MCP server for programmatically managing and operating Jupyter notebooks, providing functions such as reading, editing, and executing notebook cells, and supporting integration with Claude Desktop.

The Databricks MCP Server is a service that implements the Model Completion Protocol (MCP), providing the ability to access Databricks functions via the MCP protocol, enabling LLM tools to interact with Databricks clusters, jobs, notebooks, etc.

A Model Context Protocol (MCP) server implemented for Microsoft OneNote, providing a standardized interface for AI language models to interact with OneNote and supporting management functions for notebooks, sections, and pages.

The MCP Notebook Service is a server for progressive execution of Python code. It retains variable states to support subsequent execution and needs to run in a Docker environment to ensure system security.

A Kaggle MCP service based on NodeJS for exploring datasets and creating notebooks

The Neemee MCP client library is a TypeScript library for interacting with the Neemee personal knowledge management system through the Model Context Protocol (MCP). It supports two transport modes, HTTP and STDIO, provides tool APIs for creating, updating, searching notes and notebooks, as well as resource APIs for obtaining system information and resource lists, and includes complete TypeScript type support and error handling mechanisms.