Stop a Jupyter kernel and permanently remove it along with all its state.
MIT
204,700 tools. Last updated 2026-06-15 01:18
"Jupyter" matching MCP tools:
- Retrieve comprehensive status details for a specified Jupyter kernel, including execution state and resource usage.MIT
- Read Jupyter notebooks with cell outputs to review code execution results and analysis data from .ipynb files.MIT
- Execute code on a Jupyter kernel through websocket channels. Provide kernel ID and code; timeout is optional.MIT
- Add a new file to a QuantConnect project. Specify the project ID, file name, and optional content to create Python scripts, C# files, or Jupyter notebooks.Apache 2.0
- Query Jupyter notebook information and metadata, including source code, server status, sessions, and cell positions.Apache 2.0
Matching MCP Servers
- AlicenseAqualityDmaintenanceEnables 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.Last updated442Apache 2.0
- AlicenseAqualityAmaintenanceEnables interaction with Jupyter notebooks through the Model Context Protocol, supporting code execution and markdown insertion within JupyterLab environments.Last updated141,148BSD 3-Clause
- Apply multiple find-and-replace edits to a single file in one atomic operation, ensuring all changes succeed or none are applied.MIT
- Add, edit, or delete code and markdown cells in Jupyter notebooks, with optional immediate execution.Apache 2.0
- Initialize a Jupyter notebook by creating it if needed and connecting to a specified server URL. Must be called before any other notebook operations.Apache 2.0
- Generate and customize Jupyter notebooks for Python and Markdown tasks, ensuring unique names and valid JSON content for streamlined data analysis and integration with SingleStore databases.MIT
- Connect to a remote Jupyter server to run code on remote compute, GPUs, or data while keeping notebooks saved locally.MIT
- Convert a Jupyter notebook into a single Python script string with # %% cell markers for analysis, diffing, or programmatic use.MIT
- Execute code directly in Jupyter notebooks for debugging, profiling, and temporary calculations without saving to the notebook.BSD 3-Clause
- Retrieve all available Jupyter kernel sessions with IDs, names, states, and specifications to monitor resources and identify kernels for connection.BSD 3-Clause
- Insert a code cell into a Jupyter notebook at a specified position and execute it immediately with configurable timeout settings.BSD 3-Clause
- Execute code cells or install packages in a Jupyter notebook. Requires prior notebook setup to specify the server URL.Apache 2.0
- Read Jupyter notebook cells to analyze structure, view content, and identify cells for operations like deletion or insertion using brief or detailed formats.BSD 3-Clause
- Read a Jupyter notebook and retrieve its full structure including cell IDs, types, source, execution counts, and outputs.MIT
- Access and read files from the local filesystem to analyze content, supporting large files with optional line-based control for efficient data retrieval.MIT
- List all running Jupyter kernels to inspect their id, name, state, and connections.MIT