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Query Spark History Server apps, jobs, stages, and metrics in natural language.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Apache Spark History Server MCP" yet — see the docs or source repo.
Query the Spark History Server for the 10 longest-running jobs in the past week. List their application names, durations, retry/failure status, and summarize possible performance bottlenecks.
A ranked list of slow jobs with key performance metrics and a brief bottleneck analysis.
Find all failed Spark stages from yesterday, grouped by application. Show failure counts, error patterns, and whether they are concentrated on specific executors or nodes.
A grouped report of failed stages, including error distribution and suspicious node patterns.
Compare the execution performance of two specified Spark applications, focusing on job duration, stage counts, task distribution, and resource usage differences, then provide optimization suggestions.
A comparison report highlighting key differences and actionable optimization recommendations.
Search and analyze Spark Desktop meeting transcripts and emails with natural language.
Query Apache Iceberg lakehouse metadata, history, and time-travel SQL in natural language.
Let AI query semantic data through SPARQL endpoints with caching and flexible outputs.
Query S3 data lakes in natural language for discovery, analysis, and metadata exploration.
Explore Databricks metadata, run SQL, and analyze lineage for data discovery.
Interactively analyze lakehouse data with PySpark, Livy sessions, and Spark SQL.