F
licenseNot graded
qualityD
maintenanceEnables AI agents to execute Jupyter notebook cells with persistent kernel state, output persistence, and structured JSON control surface.
2
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ipynb-mcp
by YmSaki
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TDQS
A3.7/5.0
Scored across 6 tools
Disambiguation5/5
Each tool targets a distinct operation: reading metadata, reading a cell, adding, editing, running, or restarting the kernel. There is minimal overlap and an agent can clearly select the right tool for the intended action.
Naming Consistency4/5
Most tools follow a clear verb_noun pattern: read_cell, add_cell, edit_cell, run_cell, restart_kernel. notebook_info is the only slight deviation, being noun_noun rather than get_notebook_info, but it remains readable and consistent with the overall style.
Tool Count5/5
Six tools is a well-scoped set for notebook manipulation. Each tool serves a clear and necessary purpose without unnecessary bloat.
Completeness3/5
The core lifecycle of reading, adding, editing, and executing cells is covered, and restart_kernel handles execution-state resets. However, a delete_cell operation is missing, which is a notable gap for editing workflows, and there is no way to reorder cells.
Maintenance
ActivityMaintained
ResponsivenessNo issues