mcp apache spark history server
pipStandardExposes 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.
132410Updated Yesterday
Overview
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.
Installation
1Install the package
pip
pip install mcp-apache-spark-history-server2Add to Claude
Add this configuration to your claude_desktop_config.json:
claude_desktop_config.json
{
"mcpServers": {
"kubeflow-mcp-apache-spark-history-server-github": {
"command": "uvx",
"args": [
"pip install mcp-apache-spark-history-server"
]
}
}
}3Verify installation
Restart Claude Desktop, then ask:
"What tools do you have available from mcp apache spark history server?"
Prerequisites
- Python 3.10 or higher
- pip or uv package manager
- Claude Desktop or Claude API access
Configuration
No configuration required. This server works out of the box.
Usage Examples
List Resources
"What resources are available in mcp apache spark history server?"
Claude will query available resources and return a list of what you can access.
Get Details
"Show me details about [specific item] in mcp apache spark history server"
Claude will fetch and display detailed information about the requested item.
Create New
"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.
Works with mcp apache spark history server
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