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Manage Deriva catalogs and run ML workflows with versioning and feature control.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Deriva MCP Server" yet — see the docs or source repo.
Connect to the Deriva catalog, list all datasets and their current versions, and create a new version for a specified dataset with change notes.
A dataset version inventory is returned, and a new version record with change notes is created.
Review the controlled vocabulary for sample types in Deriva, identify duplicate or inconsistent entries, suggest standardization, and apply the updates.
A list of vocabulary issues, standardization suggestions, and the updated vocabulary are provided.
Run a machine learning feature generation workflow on a specified experiment dataset, write the generated features back to Deriva, and log the parameters and result summary.
Feature computation and write-back are completed, with workflow parameters, status, and a result summary returned.
Secure file and directory operations for autonomous AI development workflows.
Lets AI query and manage Microsoft Dataverse data, metadata, and environments.
Explore Databricks metadata, run SQL, and analyze lineage for data discovery.
Connect to DataHub catalogs to find datasets, trace lineage, and read metadata.
Map natural language to typed IDs and retrieve catalog and verification details.
Monitor industrial process data and get anomaly analysis with actionable recommendations.