•1 min read•from Data Science
Claude Code finally works fine with Jupyter
Our take
After a challenging experience last year, Claude Code now integrates seamlessly with Jupyter, thanks to the open-source Jupyter MCP Server. Following some initial setup, I discovered that Claude can directly communicate with my live IPython kernel, enabling it to edit notebook cells without corrupting the JSON structure. This improvement allows Claude to autonomously write, run, debug, and resolve errors, only alerting me when everything is functioning smoothly.
Last year, I've had bad experiences of using Jupyter with Claude Code. Many others told me the same.
Recently, I tried it with the open source Jupyter MCP Server (no affiliation). Setup took a bit of fiddling, but once it was up, it worked really well.
The big difference is kernel access. Claude can now talk directly to my live IPython kernel and edit notebook cells properly (without messing the JSON).
I just let it write notebooks, run top to bottom, debug & fix errors & only ping me when everything is working.
Has anybody tried JupyterLab AI extensions (jupyter-ai, notebook-intelligence etc.) ? I wonder how those compare to my Jupyter MCP based workflow.
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#rows.com#financial modeling with spreadsheets#business intelligence tools#no-code spreadsheet solutions#big data management in spreadsheets#cloud-based spreadsheet applications#workflow automation#big data performance#Claude Code#Jupyter#Jupyter MCP Server#notebooks#open source#IPython kernel#JupyterLab#notebook cells#AI extensions#kernel access#jupyter-ai#notebook-intelligence