acrolinx

Author: cephalin

articles/app-service/tutorial-ai-agent-web-app-langgraph-foundry-python.md

@@ -100,7 +100,7 @@ The `FoundryTaskAgent` is initialized in the constructor of *src/agents/foundry_
 
 This initialization code doesn't define any functionality for the agent, because you would typically build the agent in the Azure AI Foundry portal. As part of the example scenario, it also follows the OpenAPI pattern shown in [Add an App Service app as a tool in Azure AI Foundry Agent Service (Python)](tutorial-ai-integrate-azure-ai-agent-python.md), and makes its CRUD functionality available as an OpenAPI endpoint. This lets you add it to the agent later as a callable tool.
 
-The OpenAPI code is defined in *src/routes/api.py*. For example, the "GET /tasks" route defines a custom `operation_id` in the ourter parmeter, as required by the [OpenAPI spec tool in Azure AI Foundry](/azure/ai-foundry/agents/how-to/tools/openapi-spec#prerequisites), and `description` helps the agent determine how to call the API:
+The OpenAPI code is defined in *src/routes/api.py*. For example, the "GET /tasks" route defines a custom `operation_id` parameter, as required by the [OpenAPI spec tool in Azure AI Foundry](/azure/ai-foundry/agents/how-to/tools/openapi-spec#prerequisites), and `description` helps the agent determine how to call the API:
 
 :::code language="csharp" source="~/app-service-agentic-langgraph-foundry-python/src/routes/api.py" range="27-42" highlight="4-5" :::
 

articles/app-service/tutorial-ai-integrate-azure-ai-agent-dotnet.md

@@ -23,7 +23,7 @@ If your web application already has useful features, like shopping, hotel bookin
 > * Add OpenAPI functionality to your web app.
 > * Make sure OpenAPI schema compatible with Azure AI Foundry Agent Service.
 > * Register your app as an OpenAPI tool in Azure AI Foundry Agent Service.
-> * Test your agent in the the agents playground.
+> * Test your agent in the agents playground.
 
 ## Prerequisites
 

articles/app-service/tutorial-ai-integrate-azure-ai-agent-java.md

@@ -23,7 +23,7 @@ If your web application already has useful features, like shopping, hotel bookin
 > * Add OpenAPI functionality to your web app.
 > * Make sure OpenAPI schema compatible with Azure AI Foundry Agent Service.
 > * Register your app as an OpenAPI tool in Azure AI Foundry Agent Service.
-> * Test your agent in the the agents playground.
+> * Test your agent in the agents playground.
 
 ## Prerequisites
 

articles/app-service/tutorial-ai-integrate-azure-ai-agent-node.md

@@ -23,7 +23,7 @@ If your web application already has useful features, like shopping, hotel bookin
 > * Add OpenAPI functionality to your web app.
 > * Make sure OpenAPI schema compatible with Azure AI Foundry Agent Service.
 > * Register your app as an OpenAPI tool in Azure AI Foundry Agent Service.
-> * Test your agent in the the agents playground.
+> * Test your agent in the agents playground.
 
 ## Prerequisites
 

articles/app-service/tutorial-ai-integrate-azure-ai-agent-python.md

@@ -13,7 +13,7 @@ ms.service: azure-app-service
 
 # Add an App Service app as a tool in Azure AI Foundry Agent Service (Python)
 
-In this tutorial, you'll learn how to expose an FastAPI app's functionality through OpenAPI, add it as a tool to Azure AI Foundry Agent Service, and interact with your app using natural language in the agents playground.
+In this tutorial, you'll learn how to expose a FastAPI app's functionality through OpenAPI, add it as a tool to Azure AI Foundry Agent Service, and interact with your app using natural language in the agents playground.
 
 If your web application already has useful features, like shopping, hotel booking, or data management, it's easy to make those capabilities available to an AI agent in Azure AI Foundry Agent Service. By simply adding an OpenAPI schema to your app, you enable the agent to understand and use your app's capabilities when it responds to users' prompts. This means anything your app can do, your AI agent can do too, with minimal effort beyond creating an OpenAPI endpoint for your app. In this tutorial, you start with a simple restaurant ratings app. By the end, you'll be able to see restaurant ratings as well as create new restaurants and new reviews with an agent through conversational AI.
 
@@ -23,7 +23,7 @@ If your web application already has useful features, like shopping, hotel bookin
 > * Add OpenAPI functionality to your web app.
 > * Make sure OpenAPI schema compatible with Azure AI Foundry Agent Service.
 > * Register your app as an OpenAPI tool in Azure AI Foundry Agent Service.
-> * Test your agent in the the agents playground.
+> * Test your agent in the agents playground.
 
 ## Prerequisites
 

articles/app-service/tutorial-ai-model-context-protocol-server-python.md

@@ -13,7 +13,7 @@ ms.service: azure-app-service
 
 # Integrate an App Service app as an MCP Server for GitHub Copilot Chat (Python)
 
-In this tutorial, you'll learn how to expose an FastAPI app's functionality through Model Context Protocol (MCP), add it as a tool to GitHub Copilot, and interact with your app using natural language in Copilot Chat agent mode.
+In this tutorial, you'll learn how to expose a FastAPI app's functionality through Model Context Protocol (MCP), add it as a tool to GitHub Copilot, and interact with your app using natural language in Copilot Chat agent mode.
 
 :::image type="content" source="media/tutorial-ai-model-context-protocol-server-python/model-context-protocol-call-success.png" alt-text="Scenario Preview: Screenshot showing that the response from the MCP tool call in the GitHub Copilot Chat window.":::
 
@@ -160,7 +160,7 @@ At a minimum, open the [sample application](https://github.com/Azure-Samples/msd
     - The `@mcp.tool()` decorator adds a [tool](https://github.com/modelcontextprotocol/python-sdk?tab=readme-ov-file#tools) to the MCP server with its implementation.
     - The tool function's description helps the calling agent to understand how to use the tool and its parameters.
 
-    The tools duplicate the existing restaurant reviews functionality in the form-based FastAPI web application. If you want, you can add more tools for update and delete funcionality.
+    The tools duplicate the existing restaurant reviews functionality in the form-based FastAPI web application. If you want, you can add more tools for update and delete functionality.
 
 1. In *src/fastapi_app/app.py*, find the line for `app = FastAPI()` (line 24) and replace it with the following code:
 
@@ -170,7 +170,7 @@ At a minimum, open the [sample application](https://github.com/Azure-Samples/msd
     app.mount("/mcp", mcp.streamable_http_app())
     ```
 
-    This code mounts the MCP server's streamable HTTP endpoint to the existing FastAPI app at the the path `/mcp`. Together with the default path of the streamable HTTP endpoint, the full path is `/mcp/mcp`.
+    This code mounts the MCP server's streamable HTTP endpoint to the existing FastAPI app at the path `/mcp`. Together with the default path of the streamable HTTP endpoint, the full path is `/mcp/mcp`.
 
 ## Test the MCP server locally