$ loading_
Provides Spark query plans and catalog data for optimization and discovery.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "PySpark MCP Server" yet — see the docs or source repo.
Analyze this Spark SQL query using available query plans and catalog info, then suggest performance optimizations: SELECT ...
A query plan analysis, bottleneck diagnosis, and actionable optimization suggestions.
List tables, fields, and partition info in the current Spark catalog related to user profiles, and explain suitable analysis scenarios.
Relevant table schemas, field descriptions, and suitable analytics use cases.
Inspect this Spark job’s query plan and metadata to determine why execution is slow or shuffle-heavy, and provide troubleshooting steps.
Root-cause analysis, debugging steps, and remediation advice.
Connect AI to any SPARQL endpoint for querying and updating RDF data.
Search and analyze Spark Desktop meeting transcripts and emails with natural language.
Query structured data in natural language without needing SQL or API expertise.
Query Spark History Server apps, jobs, stages, and metrics in natural language.
Query Databricks datasets in natural language and answer business questions without SQL.
Connect to StarRocks via MCP for querying, analysis, and database integration.