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Access Zeppelin APIs to manage and run data engineering notebooks and paragraphs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "zeppelin-mcp" yet — see the docs or source repo.
Connect to Zeppelin, list all notebooks under the specified project, filter those with names containing "daily_etl", run them one by one, and return each notebook's execution status and failed paragraphs.
A batch execution report with matched notebooks, run statuses, failed paragraphs, and error details.
Inspect the most recently failed paragraph in the notebook "sales_pipeline", read its content, output, and interpreter, and provide possible troubleshooting clues.
A detailed summary of the failed paragraph and initial diagnostic suggestions for troubleshooting.
List available Zeppelin interpreters, check the Spark interpreter status, and if it is not ready, try restarting it and summarize the status changes before and after.
An interpreter list, Spark status check result, and a summary of the restart action and final state.
Let AI agents manage and run Apache Zeppelin notebooks through the API.
Connect to Jupyter via MCP to run code and explore data interactively.
Let AI read, edit, and execute Jupyter notebooks directly.
Connect and manage Jupyter notebooks for interactive coding, analysis, and visualization.
Connect to the mcp API via MCP to extend AI tool capabilities.
Build, debug, and manage software tasks with natural language across LLMs.