JupyterMCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pingA | Simple ping command to check server connectivity |
| insert_and_execute_cellA | Insert a cell at the specified position and execute it, and optionally set slideshow type. If code cell, it will be executed. If markdown cell, it will be rendered. |
| save_notebookA | Save the current Jupyter notebook |
| get_cells_infoB | Get information about all cells in the notebook |
| get_notebook_infoB | Get information about the current Jupyter notebook |
| run_cellC | Run a specific cell by its index |
| run_all_cellsA | Restart and run all cells in the notebook. You need to wait for user approval |
| get_cell_text_outputA | Get the text output content of a specific code cell by its index |
| get_image_outputA | Get image outputs from a specific cell by its index |
| edit_cell_contentA | Edit the content of a specific cell by its index and optionally execute it |
| set_slideshow_typeA | Set the slideshow type for a specific cell by its index |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose: editing, inserting, running cells individually or all at once, retrieving text or image outputs, getting notebook info, saving, and slideshow settings. No two tools overlap significantly.
Tool names follow a consistent verb_noun pattern (e.g., edit_cell_content, get_cells_info, run_cell). 'ping' is a simple exception but is widely recognized and does not disrupt overall consistency.
With 11 tools, the set is well-scoped for interacting with a Jupyter notebook. It covers navigation, editing, execution, output retrieval, slideshow, and saving without being bloated or sparse.
The tool surface covers core notebook operations (edit, insert, run, save, slideshow, output retrieval) but lacks cell deletion, reordering, or kernel management. These are minor gaps for typical workflows.