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mcp-apache-spark-history-server

Verified Safe

by kubeflow

Overview

Connects AI agents to Apache Spark History Server for intelligent job analysis and performance monitoring.

Installation

Run Command
uvx --from mcp-apache-spark-history-server spark-mcp

Environment Variables

  • SHS_MCP_CONFIG
  • SHS_MCP_PORT
  • SHS_MCP_DEBUG
  • SHS_MCP_ADDRESS
  • SHS_MCP_TRANSPORT
  • SHS_SERVERS_*_URL
  • SHS_SERVERS_*_AUTH_USERNAME
  • SHS_SERVERS_*_AUTH_PASSWORD
  • SHS_SERVERS_*_AUTH_TOKEN
  • SHS_SERVERS_*_VERIFY_SSL
  • SHS_SERVERS_*_TIMEOUT
  • SHS_SERVERS_*_EMR_CLUSTER_ARN
  • SHS_SERVERS_*_INCLUDE_PLAN_DESCRIPTION

Security Notes

The project demonstrates strong security practices, including a pre-commit hook (`check-config-security.py`) to prevent hardcoded credentials, configurable SSL verification for HTTP requests, and the use of environment variables/Kubernetes secrets for sensitive data. The `SparkHtmlClient` uses Playwright to render external Spark UI content in a sandboxed browser environment; while direct user control over screenshot `save_path` is not exposed in the API, the design generally prioritizes secure handling of external interactions. A comprehensive `SECURITY.md` policy is in place. No 'eval' or malicious patterns were found in the provided code.

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Stats

Interest Score60
Security Score9
Cost ClassMedium
Avg Tokens1000
Stars111
Forks36
Last Update2025-12-10

Tags

sparkmcpanalyticsperformanceai-agents