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 3021244161
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TDQS
A3.6/5.0
Scored across 6 tools
Disambiguation5/5
Each tool targets a clearly distinct action on a notebook: read, edit, run, poll run status, cancel run, and manage kernels. The run_status/run_cancel pair are explicitly scoped to background runs started by notebook_run, so there is no real misselection risk.
Naming Consistency5/5
All six tools use a uniform snake_case notebook_* prefix with a predictable verb/noun suffix (read, edit, run, run_status, run_cancel, kernel). The pattern is consistent throughout with no style deviations.
Tool Count5/5
Six tools is well-scoped for a notebook server, covering the core read/edit/execute workflow plus async run lifecycle and kernel management. No tool feels redundant or padded.
Completeness4/5
Read, edit, run, and kernel lifecycle are covered, including async run polling and cancellation. Minor gaps remain, such as creating a brand-new notebook file or deleting cells/notebooks explicitly, but these are largely workable via edit.
Maintenance
ActivityMaintained
ResponsivenessUnresponsive