Model Context Protocol (MCP) server for Apache Spark History Server with job comparison and analytics
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# Kubeflow Spark AI Toolkit [](https://github.com/kubeflow/mcp-apache-spark-history-server/actions) [](https://www.python.org/downloads/) [](https://modelcontextprotocol.io/) [](https://opensource.org/licenses/Apache-2.0) [](https://github.com/kubeflow) [](https://cloud-native.slack.com/archives/C09FRRM6QM7) > **Connect AI agents and engineers to Apache Spark History Server for intelligent job analysis, performance monitoring, and investigation** --- > [!IMPORTANT] > ### ✨ NEW — Spark History Server CLI is now available > [](skills/cli/README.md) > > A standalone Go binary that queries Spark History Server **directly from your terminal** — no MCP, no AI framework, no daemon process. Inspect jobs, compare runs, investigate failures, and script against the Spark REST API. > > **[Get started with the SHS CLI →](skills/cli/README.md)** --- This project provides **two interfaces** to your Spark History Server data: | | 🛠️ [SHS CLI (`shs`)](#️-shs-cli-shs--for-engineers--scripts) | ⚡ [MCP Server](#-mcp-server--for-ai-agents) | |---|---|---| | **For** | Engineers, shell scripts, CI/CD, coding agents | AI agents and MCP-compatible clients | | **Mental model** | "I know the command I want to run" | "Agent, investigate this Spark app" | | **Install** | Single static binary — no dependencies | Python 3.12+, uv | | **Get started** | [CLI docs →](skills/cli/README.md) | [MCP do…
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