Exposes Apache Spark History Server data to AI agents. Provides job history, logs, and performance metrics. Connects to Spark clusters via REST API. Used by developers to analyze job performance, debug issues, and optimize Spark applications.
Exposes Apache Spark History Server data to AI agents. Provides job history, logs, and performance metrics. Connects to Spark clusters via REST API. Used by developers to analyze job performance, debug issues, and optimize Spark applications.
pip install mcp-apache-spark-history-serverAdd this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"kubeflow-mcp-apache-spark-history-server-github": {
"command": "uvx",
"args": [
"pip install mcp-apache-spark-history-server"
]
}
}
}Restart Claude Desktop, then ask:
"What tools do you have available from mcp apache spark history server?"
No configuration required. This server works out of the box.
"What resources are available in mcp apache spark history server?"
Claude will query available resources and return a list of what you can access.
"Show me details about [specific item] in mcp apache spark history server"
Claude will fetch and display detailed information about the requested item.
"Create a new [item] in mcp apache spark history server with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
We build custom MCP integrations for B2B companies. From simple connections to complex multi-tool setups.