by kubeflow
MCP Server for Apache Spark History Server. The bridge between Agentic AI and Apache Spark.
# Add to your Claude Code skills
git clone https://github.com/kubeflow/mcp-apache-spark-history-server🤖 Connect AI agents to Apache Spark History Server for intelligent job analysis and performance monitoring
Transform your Spark infrastructure monitoring with AI! This Model Context Protocol (MCP) server enables AI agents to analyze job performance, identify bottlenecks, and provide intelligent insights from your Spark History Server data.
Spark History Server MCP bridges AI agents with your existing Apache Spark infrastructure, enabling:
📺 See it in action:
graph TB
A[🤖 AI Agent/LLM] --> F[📡 MCP Client]
B[🦙 LlamaIndex Agent] --> F
C[🌐 LangGraph] --> F
D[�️ Claudep Desktop] --> F
E[🛠️ Amazon Q CLI] --> F
F --> G[⚡ Spark History MCP Server]
G --> H[🔥 Prod Spark History Server]
G --> I[🔥 Staging Spark History Server]
G --> J[🔥 Dev Spark History Server]
H --> K[📄 Prod Event Logs]
I --> L[📄 Staging Event Logs]
J --> M[📄 Dev Event Logs]
🔗 Components:
The package is published to PyPI: https://pypi.org/project/mcp-apache-spark-history-server/
git clone https://github.com/kubeflow/mcp-apache-spark-history-server.git
cd mcp-apache-spark-history-server
# Install Task (if not already installed)
brew ins...