"Headroom open-notebook resources" matching MCP servers:

Enables agents to open or connect to a Colab browser tab and use notebook tools, resources, prompts, and progress through a local stdio session.

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.

A Model Context Protocol (MCP) server that provides comprehensive Jupyter notebook interaction capabilities, compatible with Claude Code.

Enables agents to browse, create, edit, and execute Jupyter notebook cells against local .ipynb files or a running Jupyter Server, including kernel interrupt/restart and notebook export. Outputs (text, tables, PNG images) are written back to the notebook and returned to the conversation.

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

Lightweight Python Notebook MCP - Enable AI assistants to create, edit, and view Jupyter notebooks via Model Context Protocol

Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.

Enables AI agents to create, read, edit, and execute Jupyter notebook cells, manage kernels, and connect to remote Jupyter servers.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

Connects Jupyter Notebook to Claude AI for direct notebook control and code execution.

An MCP server that enables LLMs to execute Python code on GPU-accelerated compute nodes within SLURM-managed HPC environments. It bridges local clients to remote clusters by launching JupyterLab sessions via SLURM jobs to facilitate high-performance notebook-based computation.

Enhanced fork of Google's Colab MCP, pre-registers all 7 notebook tools at startup (get_cells, add/run/update/delete/move_cell, add_text_cell), adds programmatic GPU control (T4/L4/A100) via OAuth, and fixes the "Disconnected from local server" issue with IPv4-only bind, PNA CORS headers, and stale-tab dedup. Works on Chrome, Edge, Windows, macOS, Linux.

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.

Integrates Neovim buffers with Claude, enabling real-time buffer awareness and direct in-editor content updates through MCP resources and tools.

The most powerful open-source Cairo code generator.

A template for building Model Context Protocol servers that allow AI assistants to interact with custom data and services through queryable resources and specialized tools.

A production-ready FastMCP server template with modular architecture for building MCP servers with organized tools, resources, and prompts, featuring container support and AI agent documentation system.

A TypeScript starter template for building MCP servers with example tools (echo, math operations, time, flight status) and resources (server info, greetings). Provides a modular architecture for easily extending with custom tools and resources.

Enables running Jupyter notebooks on temporary AWS compute (EC2 + SSM) with cost estimation, dry-run planning, progress reporting, and automatic cleanup.

Lets any MCP-compatible agent use Google Colab or Jupyter runtimes as an execution backend, enabling code execution, notebook management, package installation, hardware introspection, training jobs, and file handling.

A comprehensive TypeScript boilerplate MCP server featuring domain-driven design and dynamic component loading. Provides example tools for calculations and text processing, system resources, and writing assistance prompts.

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

A Model Context Protocol server that gives Codex and other MCP clients access to Google Colab runtimes—allowing session allocation, command execution, notebook management, file operations, and data transfers.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

An MCP server that bridges local AI agents to Google Colab notebooks, enabling execution of Python code and interaction with notebook states directly from the agent.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

A simple MCP server that provides a tool to fetch current weather information for cities using the Open-Meteo API, communicating through stdin/stdout.

Local-first MCP server for controlling Google Colab as a development, shell, file, and training runtime, with tools for notebook editing, GPU acceleration, and file transfer.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.

A local stdio MCP server that lets agents submit and manage Python/notebook jobs on Kaggle and Google Colab, with quota-aware provider recommendation, job listing/reconciliation, downloads, and cancellation. It runs in a safe mock mode by default and requires double-gated flags before any real GPU or CCU-billed work is submitted.