"Jupyter" matching MCP servers:

A self-hosted MCP server providing Claude with an interactive Jupyter environment, including real kernels, persistent notebooks, and optional GPU offload to Google Colab.

Enables Codex to connect to a locally running JupyterLab instance and use its notebook tools through MCP, allowing tasks such as reading and executing notebooks.

Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.

AI-powered MCP server for connecting and managing Jupyter Notebooks. Enables interactive code execution, multi-notebook management, and multimodal output for data analysis, visualization, and machine learning.

Enables programmatic interaction with Jupyter notebooks, allowing reading, editing, and executing cells via Claude.

Enables interaction with Jupyter notebooks through the Model Context Protocol, supporting code execution and markdown insertion within JupyterLab environments.

An MCP server for programmatically editing Jupyter notebooks, offering 29 tools for reading, modifying, and batch-processing notebooks without requiring a Jupyter server.

An MCP server that connects directly to a Jupyter kernel via ZMQ, enabling AI assistants to read, create, edit, execute, and manage Jupyter Notebooks as MCP tools.

Enables inspection and editing of Jupyter notebook files (.ipynb) through tools for reading, adding, updating, deleting, moving, and converting cells while preserving metadata.

Exposes Jupyter notebook operations as MCP tools over plain HTTP, allowing AI agents to explore, edit, run, and debug notebooks in a live VS Code session using local or remote kernels.

VS Code extension that bridges local Jupyter Notebooks with AI Agents via MCP, enabling direct control of the active notebook tab.

An MCP server that enables AI to connect and manage Jupyter Notebooks in real-time, with support for cell operations, execution, and multimodal outputs.

A configurable MCP server extension for Jupyter Server that enables dynamic registration of Python functions as tools accessible to MCP clients from a running Jupyter Server.

Automates Jupyter Book notebook creation by fixing common rendering issues (bold, math, markdown formatting) and provides tools for adding cells, validating notebooks, updating TOC, and deploying.

Enables an agent to run shell commands through a JupyterLab/JupyterHub-hosted terminal, using REST API and WebSocket via Selenium for session handling, when SSH is not available.

A FastMCP server for loading, editing, searching, and saving Jupyter notebooks (.ipynb) through MCP tools. It maintains a single active notebook session with live cell indices that update as cells are inserted or removed.

Execute Python code with persistent state across Claude conversations using a background Jupyter kernel. Supports creating notebooks, managing virtual environments, and maintaining variables/imports between code executions.

A Model Context Protocol server for comprehensive Jupyter notebook manipulation, featuring position-based cell operations and bulk editing. It includes specialized integration for VS Code to synchronize notebook changes and trigger file reloads.

Provides tools for interacting with Jupyter notebooks, allowing users to read, add, and execute notebook cells. It supports full notebook execution and metadata retrieval through the FastMCP framework.