chore: import upstream snapshot with attribution

2026-07-13 13:39:25 +08:00
commit db620d33df
5151 changed files with 925932 additions and 0 deletions
@@ -0,0 +1,67 @@
+# Getting started with Model Content Protocol
+
+The getting started with Model Content Protocol samples demonstrate how to use MCP Server tools from an agent.
+
+## Getting started with agents prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 10.0 SDK or later
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
+
+**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
+
+**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Samples
+
+|Sample|Description|
+|---|---|
+|[Agent with MCP server tools](./Agent_MCP_Server/)|This sample demonstrates how to use MCP server tools with a simple agent|
+|[Agent with MCP server tools and authorization](./Agent_MCP_Server_Auth/)|This sample demonstrates how to use MCP Server tools from a protected MCP server with a simple agent|
+|[Agent with per-run MCP authentication headers](./Agent_MCP_PerRun_AuthHeaders/)|This sample demonstrates how to attach per-run, refreshable authentication headers to MCP requests using a custom HttpClient handler and an AsyncLocal scope. Uses Microsoft Foundry (`FOUNDRY_PROJECT_ENDPOINT` / `FOUNDRY_MODEL`) rather than the Azure OpenAI variables in the prerequisites above.|
+|[Responses Agent with Hosted MCP tool](./ResponseAgent_Hosted_MCP/)|This sample demonstrates how to use the Hosted MCP tool with the Responses Service, where the service invokes any MCP tools directly|
+|[Agent with long-running MCP task (transparent polling)](./Agent_MCP_LongRunningTask_Client/)|This sample demonstrates how an agent transparently drives a long-running MCP task (SEP-2663) to completion. The wrapper polls the task internally on both `RunAsync` and `RunStreamingAsync` invocations.|
+
+## Running the samples from the console
+
+To run the samples, navigate to the desired sample directory, e.g.
+
+```powershell
+cd Agents_Step01_Running
+```
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+```
+
+If the variables are not set, you will be prompted for the values when running the samples.
+
+Execute the following command to build the sample:
+
+```powershell
+dotnet build
+```
+
+Execute the following command to run the sample:
+
+```powershell
+dotnet run --no-build
+```
+
+Or just build and run in one step:
+
+```powershell
+dotnet run
+```
+
+## Running the samples from Visual Studio
+
+Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
+
+You will be prompted for any required environment variables if they are not already set.