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Run Python code securely with inline dependencies for fast experiments and analysis.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "ai.smithery/STUzhy-py_execute_mcp" MCP server from askskill: Run: claude mcp add --transport http 'ai-smithery-stuzhy-py-execute-mcp' 'https://server.smithery.ai/@STUzhy/py_execute_mcp/mcp'
Run this Python code in the sandbox, check for errors, and return the output plus fix suggestions if needed: python print(sum([1, 2, 3, 4]))
Returns the execution result, error status, and fix suggestions when needed.
Run the following Python code in a secure sandbox and use pandas to analyze this CSV data, then output summary statistics for each column: Dependency: pandas Data: name,score Alice,88 Bob,92 Cindy,95
Returns the execution result after installing dependencies, along with summary statistics or tabular analysis.
Execute the following Python code in the sandbox, identify the error cause, fix it, rerun it, and explain what changed: python nums = [1, 2, 3] print(nums[5])
Returns the original error, the fixed code, rerun output, and a brief explanation.
No documentation provided
Check the source repo for usage and examples.
Securely run Python code in a sandbox and return execution results.
Safely run Python code, capture output, and generate charts.
Run Python code securely in a sandbox and return results and files.
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 session state and file access in containers.