Dataproc
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Manages Google Cloud Dataproc clusters and jobs through a standardized Model Context Protocol interface.
About
This server provides a standardized Model Context Protocol (MCP) interface for programmatic management of Google Cloud Dataproc resources. It enables AI assistants and other automated systems to interact with Dataproc clusters and jobs, facilitating tasks such as provisioning clusters, submitting and monitoring various job types (Spark, PySpark, Hive, etc.), and orchestrating serverless batch operations, streamlining big data workflows on Google Cloud.
Key Features
- Integrate via multiple transport protocols (STDIO, HTTP, SSE)
- Orchestrate serverless Dataproc batch jobs
- 0 GitHub stars
- Submit and manage various job types (Spark, PySpark, Hive, Hadoop)
- Supports multiple Google Cloud authentication methods
- Manage Google Cloud Dataproc clusters (create, delete, get, list)
Use Cases
- Automating Google Cloud Dataproc cluster lifecycle management for AI assistants.
- Programmatically submitting and monitoring big data jobs (Spark, PySpark, etc.) on Dataproc.
- Orchestrating serverless Dataproc batch jobs for data processing pipelines.
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