Fabric Data Agent Tools
Useful tools and utilities for working with Microsoft Fabric Data Agents
Data Agent Automation Using Python SDK
Notebook to automate creation, testing and updating data agent using Python SDK in Fabric notebook.
Data Agent Client - Teams App
A Microsoft Teams application that enables natural language queries to Fabric Data Agents, featuring real-time streaming responses, DAX query visualization, and multi-agent support. - Natural Language Queries: Ask questions in plain language and get AI-powered answers from your semantic models - Multi-Agent Support: Connect to multiple Fabric Data Agents and switch between them seamlessly - Real-Time Streaming: See responses as they're generated with live progress indicators - Query Transparency: View the generated DAX code and query results for each analysis step - Teams Integration: Native Teams app experience with SSO authentication - Fluent UI Design: Modern, responsive interface following Microsoft design guidelines
Data Agent Inspector
App to review data agent diagnostic file.
Semantic Link Labs
An open-source toolkit for building semantic layers and connecting data agents to structured data sources in Microsoft Fabric.
Data Agent MCP
The Model Context Protocol (MCP) server is an emerging standard in the AI landscape that allows AI systems to discover and interact with external tools in a structured way. It plays a critical role in enabling AI models to access and use external knowledge and capabilities. By using MCP servers, AI systems can extend beyond their own data and reasoning. MCP servers provide a way to expose tools and services to AI systems in a consistent, discoverable manner. They help organizations integrate their knowledge into AI workflows.
Semantic Model Data Agent Readiness Analyzer
What it does: Automates 18+ critical checks to validate your Power BI semantic model is ready for Microsoft Fabric Data Agents — saves hours of manual validation Prevents production failures by detecting issues like missing descriptions, duplicate column names, implicit measures, and poor DAX performance before deployment Provides actionable scoring with severity-weighted prioritization (🔴 Critical → 🟡 Recommended) so you know exactly what to fix first Aligned with official Microsoft guidance — covers 100% of the Fabric Data Agent Checklist including security requirements, AI Data Schema validation, and performance optimization Version-controlled best practices — guides you on Prep for AI configuration (Verified Answers, AI Instructions, synonyms) that travels with your PBIP model through Git and deployment pipelines Bottom line: Run this notebook before deploying your Data Agent to catch configuration gaps that would otherwise cause silent failures, poor accuracy, or timeout errors in production.