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MCP Connector: Integrating AI agent with Data Warehouse in Microsoft Fabric

LazaUK/AIFoundry-MCPConnector-FabricGraphQL · 11 stars · Python · MIT

MCP server MCP Client and Server apps to demo integration of Azure OpenAI-based AI agent with a Data Warehouse, exposed through GraphQL in Microsoft Fabric.

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README.md

MCP Connector: Integrating AI agent with Data Warehouse in Microsoft Fabric

This repo demonstrates the integration of an Azure OpenAI-powered AI agent with a Microsoft Fabric data warehouse using the Model Context Protocol (MCP), open integration standard for AI agents by Anthropic.

MCP enables dynamic discovery of tools, data resources and prompt templates (with more coming soon), unifying their integration with AI agents. GraphQL provides an abstraction layer for universal data connection. Below, you will find detailed steps on how to combine MCP and GraphQL to enable bidirectional access to enterprise data for your AI agent.

Note

In the MCP server's script, some query parameter values are hard-coded for the sake of this example. In a real-world scenario, these values would be dynamically generated or retrieved.

Table of contents:

Part 1: Configuring Microsoft Fabric Backend

  1. In Microsoft Fabric, create a new data warehouse pre-populated by sample data by clicking New item -> Sample warehouse: Step1_SampleWarehouse
  2. Next, create a GraphQL API endpoint by clicking New item -> API for GraphQL: Step2_GraphQlCreate
  3. In the data configuration of GraphQL API, choose the Trip (dbo.Trip) table: Step3_GraphQLData.png
  4. Copy the endpoint URL of your GraphQL API: Step4_GraphQLDataURL.png

Part 2: Configuring Local Client Environment

  1. Install the required Python packages, listed in the provided requirements.txt:
pip install -r requirements.txt
  1. Configure environment variables for the MCP client:
Variable Description
AOAI_API_BASE Base URL of the Azure OpenAI endpoint
AOAI_API_VERSION API version of the Azure OpenAI endpoint
AOAI_DEPLOYMENT Deployment name of the Azure OpenAI model
  1. Set the value of the AZURE_FABRIC_GRAPHQL_ENDPOINT variable with the GraphQL endpoint URL from Step 1.4 above. It will be utilised by the MCP Server script to establish connectivity with Microsoft Fabric:
Variable Description
AZURE_FABRIC_GRAPHQL_ENDPOINT Microsoft Fabric's GraphQL API endpoint

Part 3: User Experience - Gradio UI

  1. Launch the MCP client in your command prompt:
python MCP_Client_Gradio.py
  1. Click the Initialise System button to start the MCP server and connect your AI agent to the Microsoft Fabric's GraphQL API endpoint: Step5_GradioLaunch.png
  2. You can now pull and push data to your data warehouse using GraphQL's queries and mutations enabled by this MCP connector: Step5_GradioUse.png

Part 4: Demo video on YouTube

A practical demo of the provided MCP connector can be found on this YouTube video.

Facts

Kind
MCP server
Repo
LazaUK/AIFoundry-MCPConnector-FabricGraphQL
Group
Uncategorized
Stars
11
License
MIT
Language
Python
Last push
2025-07-06
Forks
7
Topics
agent, ai, azure, data-warehouse, graphql, mcp-client, mcp-server, microsoft-fabric, openai

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