"Generating PowerPoint slides from Power BI datasets in folders" matching MCP servers:

An MCP (Model Context Protocol) server that lets AI agents manage Power BI workspaces, datasets, and refreshes via natural language.

A Python-based MCP server that exposes Power BI semantic models to Claude, enabling natural-language querying of Power BI data through tools like listing workspaces, exploring datasets, executing DAX queries, and triggering refreshes.

Enables AI applications to interact with Power BI through the Model Context Protocol, supporting comprehensive API operations including data retrieval and management.

Enables interaction with Microsoft Power Automate cloud flows via Azure CLI, allowing management of flows, triggers, runs, and connections.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Local-first MCP server and Chromium extension for AI-assisted Microsoft Power Automate work, enabling users to inspect, validate, edit, run, review, and revert cloud flows using a browser session.

MCP server for Microsoft Power BI and Fabric, enabling Claude to discover workspaces, semantic models, generate and execute DAX queries, and retrieve report metadata via device-code authentication.

Enables authorized AI agents to inspect, query, create, modify, validate, refresh, and manage eligible cloud semantic models in Microsoft Fabric and Power BI through stateless Streamable HTTP.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Debug, build, and manage Microsoft Power Automate cloud flows with AI agents. Get action-level error details, build flows from natural language, trigger and resubmit runs, and operate across multiple tenants. Requires a Flow Studio MCP subscription — get an API key at https://mcp.flowstudio.app

A self-hosted MCP server that enables AI assistants to inspect and manage Microsoft Power Automate cloud flows and Dataverse records locally, using your own Azure identity.

Automates enterprise Power Platform project setup and management via MCP, reducing setup time from weeks to hours through template-based provisioning, Azure DevOps orchestration, and direct API integration.

Enables users to describe an LLM fine-tuning workload and receive ranked, cost- and runtime-optimized GPU recommendations across multiple cloud providers by estimating VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job once and receive the cheapest, fastest, or most balanced GPU hardware options across a dozen cloud providers by calculating required VRAM/FLOPs and aggregating live pricing.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning workload once and get task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, and balanced GPU recommendations across multiple cloud providers.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning workload once and get ranked, cost- and speed-optimized GPU recommendations across multiple cloud providers by estimating VRAM/FLOPs requirements.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.