JupyterMCP
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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.