Enables AI assistants to analyze Azure Data Factory costs, detect waste, and provide optimization recommendations by querying pipeline run metadata and Azure pricing.
Provides full execution and management capabilities for Microsoft Fabric Data Engineering workloads, including notebooks, pipelines, Lakehouses, and Spark jobs. It enables users to trigger runs, monitor status, manage workspace items, and configure job schedules through natural language.
An MCP server that exposes Azure Data Factory operations as tools any LLM can call — trigger pipelines, monitor runs, inspect datasets, and get factory health summaries through natural language.
Enables interaction with Azure AI Foundry services for model exploration, deployment, and performance evaluation. It provides tools for managing knowledge bases via AI Search Service, executing fine-tuning jobs, and orchestrating AI agents through natural language.
Enables AI agents to interact with Microsoft Fabric by exposing tools for managing workspaces, notebooks, SQL queries, pipelines, and Livy Spark sessions. It provides a comprehensive set of operations for data engineering and analytics tasks using standard Azure authentication.