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Safely run Python code, capture output, and generate charts.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "python-sandbox-mcp-server" yet — see the docs or source repo.
Use Python to read this sales dataset, calculate monthly total sales and year-over-year changes, and print the results as a table.
Returns execution results including a console table and key statistical findings.
Use Python to plot a line chart from the following time-series data, add a title and axis labels, and output a PNG image.
Returns the generated chart image, optionally with a brief trend summary.
Run this Python code in the sandbox, identify the error, fix it, rerun it, and show the stdout output.
Returns the error analysis, corrected code, and output from the rerun.
Run commands, manage long jobs, and transfer files in AI sandboxes.
Safely run Python code with AI and MCP tool integration.
Run Python code securely with inline dependencies for fast experiments and analysis.
Run Python and machine learning workloads remotely on CoCalc cloud infrastructure.
Statically analyze Python code structure and dependencies without running the code.
Provide AI agents a local isolated Linux sandbox for fast, safe commands.