mcp-apache-spark-history-server
Verified Safeby kubeflow
Overview
Connects AI agents to Apache Spark History Server for intelligent job analysis and performance monitoring.
Installation
uvx --from mcp-apache-spark-history-server spark-mcpEnvironment 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.
Similar Servers
mcp-grafana
Provides a Model Context Protocol (MCP) server to access Grafana instances and its ecosystem for observability and incident management tasks.
kubernetes-mcp-server
Provides a Model Context Protocol (MCP) interface for AI agents to interact with and manage Kubernetes and OpenShift clusters.
mcpcat-typescript-sdk
MCPcat is an analytics platform designed for MCP server owners to capture user intentions and behavior patterns, offering session replay, trace debugging, and integration with existing observability tools.
alibabacloud-observability-mcp-server
Provide AI-driven observability insights by integrating with Alibaba Cloud monitoring services through a Model Context Protocol (MCP) server.