"Jupyter" matching MCP servers:

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

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

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

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.

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.

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.

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.

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.

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.

Enables AI agents to read, edit, execute cells, and capture outputs from Jupyter notebooks directly within VS Code or Cursor via the Model Context Protocol.

Enables AI agents to interact with collaborative Jupyter notebooks and documents in real-time, supporting notebook operations, document editing, user awareness tracking, and session management through Jupyter's RTC capabilities.

A Model Context Protocol server implementation that provides geospatial analysis tools in Jupyter notebooks, particularly for downloading NASA Earth data granules.

Enables AI agents to safely and structurally edit Jupyter Notebook (.ipynb) files by providing tools to read, edit, add, and delete cells without corrupting the JSON structure.

Enables external agents to run, edit, create, and manage the Jupyter notebook the user is actively editing in VS Code, headlessly and without approval dialogs. Works with any MCP client and is Jupyter-optional for document operations.