A
licenseNot graded
qualityD
maintenanceEnables AI agents to read, edit, execute cells, and capture outputs from Jupyter notebooks directly within VS Code or Cursor via the Model Context Protocol.
4 npm
16
MIT
Jupyter MCP Server
by datalayer
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TDQS
A3.6/5.0
Scored across 18 tools
Disambiguation4/5
Most tools have clear, distinct purposes, especially with explicit guidance distinguishing edit_cell_source from overwrite_cell_source. The three execution-related tools (execute_cell, insert_execute_code_cell, execute_code) could be confused at first glance, but their descriptions clarify the differences.
Naming Consistency4/5
The set largely follows a verb_noun pattern (read_cell, delete_cell, move_cell, restart_notebook). Minor inconsistencies like insert_execute_code_cell and unuse_notebook break the rhythm slightly, but the pattern remains predictable overall.
Tool Count4/5
18 tools is on the heavier side but reasonable for a Jupyter notebook server covering connection, notebook lifecycle, cell operations, execution, and file/kernel browsing. The count is justified by the breadth of operations rather than redundancy.
Completeness4/5
The set covers notebook activation, cell reading/writing/execution/movement/deletion, kernel restarts, and dynamic connection. Missing operations like creating/saving notebooks or managing kernels beyond restarting are notable but do not severely undermine the core workflow.
Maintenance
ActivityActive
ResponsivenessResponsive