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Safely run Python code and manage packages for analysis and automation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Python Executor" yet — see the docs or source repo.
Use Python to read a CSV file, count missing values in each column, and show the first 10 rows. If dependencies are missing, install the required packages.
Returns execution results including missing-value counts, data preview, and any installed dependencies.
Install requests and pandas, then write Python sample code to verify they import correctly and print their versions.
Returns installation status, execution results of the test code, and version details for each library.
Write a Python script that scans all .txt files in a specified folder, counts words in each file, and saves the summary as a CSV file.
Returns the full script or execution results and produces a CSV summary by file.
Lets AI agents run Python, execute scripts, and install pip packages locally.
Safely run Python in isolated containers with MCP proxying and leaner tool context.
Run Python in Docker with package, environment, and file management.
Connect to Jupyter via MCP to run code and explore data interactively.
Run Python and machine learning workloads remotely on CoCalc cloud infrastructure.
Run Python code securely with session state and file access in containers.