kubeflow/mcp-apache-spark-history-server
MCP Server for Apache Spark History Server. The bridge between Agentic AI and Apache Spark.
This project helps data engineers and ML operations teams intelligently monitor and analyze their Apache Spark jobs. It connects AI agents to your Spark History Server, allowing you to ask questions in natural language about job performance, identify bottlenecks, compare jobs, and investigate failures. The input is your existing Spark History Server data, and the output is AI-driven insights and answers about your Spark application's execution.
135 stars. Available on PyPI.
Use this if you need to use AI agents to understand, troubleshoot, or optimize Apache Spark job performance and resource utilization.
Not ideal if you are looking for a standalone Spark monitoring solution that doesn't involve AI agents or require natural language interaction.
Stars
135
Forks
46
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 03, 2026
Commits (30d)
0
Dependencies
7
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