gpt-rag-mcp

# GPT RAG Semantic Kernel Model Context Protocol Server Part of [GPT‑RAG](https://aka.ms/gpt-rag) The GPT-RAG MCP service deploys an MCP server that is used to enable agentic features in AI Chat Applications. Documentation on the Model Context Protocol can be found here: [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro) ## Prerequisites Before deploying the application, you must provision the infrastructure as described in the [GPT-RAG](https://github.com/azure/gpt-rag) repo. This includes creating all necessary Azure resources required to support the application runtime. <details markdown="block"> <summary>Click to view <strong>software</strong> prerequisites</summary> <br> The machine used to customize and or deploy the service should have: * Azure CLI: [Install Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) * Azure Developer CLI (optional, if using azd): [Install azd](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/install-azd) * Git: [Download Git](https://git-scm.com/downloads) * Python 3.12: [Download Python 3.12](https://www.python.org/downloads/release/python-3120/) * Docker CLI: [Install Docker](https://docs.docker.com/get-docker/) * VS Code (recommended): [Download VS Code](https://code.visualstudio.com/download) </details> ##### Initialize the template: - Ensure the .azure directory is present in the root - `azd deploy` ### Deploying the app with a shell script To deploy using a script, first clone the repository, set the App Configuration endpoint, and then run the deployment script. ##### PowerShell (Windows) ```powershell $env:APP_CONFIG_ENDPOINT = "https://<your-app-config-name>.azconfig.io" cd gpt-rag-mcp .\scripts\deploy.ps1 ``` #### Instructions Post Deployment (Must be executed for MCP Server to work properly) - Navigate to App Configuration resource in Azure portal - Update `AGENT_STRATEGY` variable to `mcp` - Update `MCP_SERVER_URL` variable to `<container_app_url>/mcp` (e.g. `https://{container-app-name}.{container-app-region}.azurecontainerapps.io/mcp`) or the desired MCP Server URL (if external) - In Azure Portal, Stop Orchestrator Container App, then restart it - Open frontend URL in your browser and ask "What tools are available to you?" If the MCP Server is working properly, it will list tools and their functionality. ### Start MCP Model Inspector to Test MCP connection - Run the following command in bash or pwsh ```bash npx @modelcontextprotocol/inspector ``` - Click on the link displayed in terminal that says "MCP Inspector is up and running at..." - Plug in your container Application URL (found on container app overview page in Azure portal) followed by `/mcp` (e.g. `https://<container_app_name>.eastus.azurecontainerapps.io/mcp`) ## Deploy Locally - Create a directory .vscode in your root - Move launch.json into .vscode - Update the app configuration resource - Run VS Code Debugger