Exposes Spark History Server metrics and metadata as tools for LLM-based analysis of Spark applications. It enables deep optimization of Spark jobs by providing access to job summaries, stage details, SQL execution plans, and executor performance.
Exposes Spark History Server data as tools for AI agents, enabling natural language querying of Spark applications, jobs, stages, and performance metrics.
Enables comprehensive analysis of Apache Spark event logs from S3, HTTP, or local sources, providing performance metrics, resource monitoring, shuffle analysis, and automated optimization recommendations with interactive HTML reports.
Enables AI assistants to query Hadoop MapReduce job history, including job listing, details, counters, configuration, and logs via the JobHistory REST API.
Enables AI agents to access observability and evaluation data, including run history, span traces, LLM-as-judge evaluation results, and regression reports.
Enables AI assistants to interact with Delta Lake tables stored in MinIO through Spark using natural language queries. Provides read-oriented data operations on Delta Lake tables through the Model Context Protocol.
