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
Disambiguation4/5
Most tools target clearly distinct operations (read, edit, kernel management, run, run status, run cancel). The only mild overlap is the run family, where notebook_run could plausibly be assumed to return status, but the descriptions explicitly clarify that status is polled separately via notebook_run_status.
Naming Consistency4/5
All tools share a consistent notebook_ prefix with a mostly verb_noun structure (notebook_read, notebook_edit, notebook_run_status, notebook_run_cancel). notebook_kernel deviates slightly by using a noun rather than a verb, but the overall pattern is predictable and readable.
Tool Count5/5
Six tools is well-scoped for notebook lifecycle operations. Each tool covers a distinct concern (read, edit, kernel, run, status, cancel) with no redundancy and no trivially thin surface.
Completeness4/5
The surface covers the core lifecycle: reading, editing, executing, monitoring, cancelling runs, and managing kernels. Minor gaps exist around notebook creation/deletion and cell-level structural operations, but agents can work around these via editing.
Maintenance
ActivityMaintained
ResponsivenessUnresponsive