Reference for MCP Jupyter tools (kernel management, cell execution, Papermill). Use when executing notebooks, managing kernels, or running code interactively via MCP.
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| Need | Tool | Why |
|---|---|---|
| Batch validation (Python) | scripts/notebook_tools/notebook_tools.py validate | Faster, no kernel setup |
| Batch execution (Python) | scripts/notebook_tools/notebook_tools.py execute | Papermill CLI, simpler |
| Structure analysis | scripts/notebook_tools/notebook_helpers.py list --verbose | Local, instant |
| Find enrichment gaps | NotebookHelper.find_cells_needing_enrichment() | Python API |
| Cell-by-cell .NET execution | MCP execute_on_kernel | Only option (Papermill blocked) |
| Interactive debugging | MCP manage_kernel + execute_on_kernel | Live kernel state |
| Notebook read/write via API | MCP read_cells, add_cell | Remote/programmatic |
Rule: Prefer local scripts for Python notebooks. Use MCP for .NET kernels and interactive sessions. See notebook-helpers skill for full script reference.
| Tool | Description |
|---|---|
list_kernels() | List available kernel specs |
manage_kernel(action, kernel_name/id) | start/stop/restart/interrupt kernel |
execute_on_kernel(kernel_id, mode, ...) | Execute code, cell, or full notebook |
execute_notebook(input_path, ...) | Papermill execution (sync/async) |
read_notebook(path) | Read notebook content |
read_cells(path, mode) | Read cells (list/summary) |
get_notebook_info(path) | Notebook metadata |
manage_async_job(action, job_id) | Manage async Papermill jobs |
| Kernel | Name | Notes |
|---|---|---|
| Python 3 | python3 | Via ipykernel in conda mcp-jupyter-py310 |
| .NET C# | .net-csharp | Via dotnet-interactive |
| .NET F# | .net-fsharp | Via dotnet-interactive |
| Lean 4 | lean4 | Via WSL wrapper |
execute_notebook(
input_path="MyIA.AI.Notebooks/path/notebook.ipynb",
output_path="MyIA.AI.Notebooks/path/notebook.ipynb", # Same file = overwrite with outputs
mode="sync"
)
manage_kernel(action="start", kernel_name="python3")
# Execute cells
execute_on_kernel(kernel_id="...", mode="notebook_cell", path="notebook.ipynb", cell_index=0)
# ...
manage_kernel(action="stop", kernel_id="...")
IMPORTANT: Papermill does NOT work with .NET notebooks. Always use cell-by-cell.
manage_kernel(action="start", kernel_name=".net-csharp")
# CRITICAL: Set working directory first
execute_on_kernel(
kernel_id="...", mode="code",
code='System.IO.Directory.SetCurrentDirectory(@"d:\\dev\\CoursIA\\MyIA.AI.Notebooks\\Sudoku");'
)
# Execute cells sequentially
for idx in range(cell_count):
execute_on_kernel(kernel_id="...", mode="notebook_cell", path="notebook.ipynb", cell_index=idx)
manage_kernel(action="stop", kernel_id="...")
| Problem | Workaround |
|---|---|
Papermill + #!import | Use cell-by-cell execution |
| Papermill + .NET kernels | Kernel hangs at startup; use cell-by-cell |
| .NET cold start timeout | Normal (30-60s); retry once |
| Async progress values incorrect | Known bug; ignore progress numbers |
| Kernel unresponsive after failed Papermill | Stop and restart kernel |
| Relative paths fail | Set working directory explicitly |
| Widgets/interactive elements | Use BATCH_MODE=true parameter |
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Cycle 30 min du secrétaire vérificateur myia-po-2028:CoursIA-3. Atteste en tiers, du plus ancien au plus récent, les PRs ouvertes sans dossier valide (chaque READY, une fois lu et approuvé par ai-01, est mergé sans attendre son cycle), et fait circuler l'information sur workspace-CoursIA-3.
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Detect cell-ordering / enchainement problems in Jupyter notebooks (canonical-order slippage, misplaced or forgotten cells). Arguments: [target] [--severity HIGH|MED|LOW] [--json]
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