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Run Python and machine learning workloads remotely on CoCalc cloud infrastructure.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-server-cocalc-exec" yet — see the docs or source repo.
Please run this Python code in CoCalc: load a CSV file, count missing values per column, output descriptive statistics, and generate a correlation heatmap.
Returns a summary of the statistics and provides the generated chart or chart file details.
Please use Python on CoCalc to train a binary classification model: split train/test sets, train a random forest, and report accuracy, F1 score, and feature importance.
Returns model evaluation metrics, key feature explanations, and reusable training code results.
Please run this Python research computation script on CoCalc. If it fails, identify the issue, provide a fixed version, rerun it, and show the final output.
Returns the error cause, the corrected code, and the successful execution results.
Run GPU-accelerated Python on Google Colab without local hardware.
Connect to Colab so AI can run and manage cloud notebooks.
Delegate coding tasks to Codex via MCP with security and result checks.
Let AI perform calculations, search knowledge, and handle basic email tasks.
Connect to Jupyter via MCP to run code and explore data interactively.
Build and use a secure Python MCP server and client with tools and resources.