acrolinx updates

Author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/1-introduction.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.introduction
 title: Introduction
 metadata:
   title: Introduction
-  description: "Learn how to integrate MCP tools with Azure AI Agents."
+  description: "Learn how to integrate Model Context Protocol (MCP) tools with Azure AI Agents."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/2-understand-mcp-tool-discovery.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.understand-mcp-tool-discovery
 title: Understand MCP tool discovery
 metadata:
   title: Understand MCP tool discovery
-  description: "Learn how MCP servers host functions that can be discovered by LLMs."
+  description: "Learn how Model Context Protocol (MCP) servers host functions that can be discovered by LLMs."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/3-mcp-client-server-setup.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.mcp-client-server-setup
 title: Integrate agent tools using an MCP server and client
 metadata:
   title: Integrate agent tools using an MCP server and client
-  description: "Learn how to expose MCP tools through a server and register them to an Azure AI Agent."
+  description: "Learn how to expose Model Context Protocol (MCP) tools through a server and register them to an Azure AI Agent."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/4-exercise.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.exercise
 title: Exercise - Connect MCP tools to Azure AI Agents
 metadata:
   title: Exercise - Connect MCP tools to Azure AI Agents
-  description: "Build an MCP client-server application that dynamically registers tools to an Azure AI Agent."
+  description: "Build a Model Context Protocol (MCP) client-server application that dynamically registers tools to an Azure AI Agent."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/5-knowledge-check.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.knowledge-check
 title: Module assessment
 metadata:
   title: Module assessment
-  description: "Check your learning on connecting MCP tools to Azure AI Agents."
+  description: "Check your learning on connecting Model Context Protocol (MCP) tools to Azure AI Agents."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid
@@ -35,11 +35,11 @@ quiz:
       isCorrect: false
       explanation: "Incorrect. The client uses direct calls, not event subscriptions, to list tools."
   - content: "Why should MCP tools be wrapped in async functions on the client-side?"
-  choices:
+    choices:
     - content: "To allow the agent to wait for user input."
       isCorrect: false
       explanation: "Incorrect. The tools do not prevent the agent from receiving user input."
-     - content: "To enable asynchronous invocation so the agent can call tools without blocking."
+    - content: "To enable asynchronous invocation so the agent can call tools without blocking."
       isCorrect: true
       explanation: "Async functions let the agent invoke tools efficiently."
     - content: "To convert the functions into REST API endpoints automatically."

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/6-summary.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.connect-agent-to-mcp-tools.summary
 title: Summary
 metadata:
   title: Summary
-  description: "Reflect on what you learned about MCP agent tools."
+  description: "Reflect on what you learned about Model Context Protocol (MCP) agent tools."
   ms.date: 06/13/2025
   author: buzahid
   ms.author: buzahid

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/includes/1-introduction.md

@@ -1,4 +1,4 @@
-AI agents are capable of performing a wide range of tasks, but many tasks still require them to interact with tools outside the LLM. Agents may need to access APIs, databases, or internal services. Manually integrating and maintaining these tools can quickly become complex, especially as your system grows or changes frequently.
+AI agents are capable of performing a wide range of tasks, but many tasks still require them to interact with tools outside the large language model. Agents may need to access APIs, databases, or internal services. Manually integrating and maintaining these tools can quickly become complex, especially as your system grows, or changes frequently.
 
 Model Context Protocol (MCP) servers can help solve this problem by integrating with AI agents. Connecting an Azure AI Agent to a Model Context Protocol (MCP) server can provide your agent with a catalog of tools accessible on demand. This approach makes your AI solution more robust, scalable, and easier to maintain.
 

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/includes/2-understand-mcp-tool-discovery.md

@@ -12,7 +12,7 @@ This approach means:
 
 ## How does MCP enable dynamic tool discovery?
 
-An MCP server hosts a set of functions that are exposed as tools using the `@mcp.tool` decorator. Tools are a primitive type in the MCP that enable servers to expose executable functionality to clients. A client can connect to the server and fetch these tools dynamically. The client then generates function wrappers that are added to the Azure AI Agent's tool definitions. This setup creates a flexible pipeline:
+An MCP server hosts a set of functions that are exposed as tools using the `@mcp.tool` decorator. Tools are a primitive type in the MCP that enables servers to expose executable functionality to clients. A client can connect to the server and fetch these tools dynamically. The client then generates function wrappers that are added to the Azure AI Agent's tool definitions. This setup creates a flexible pipeline:
 
 - The MCP server hosts available tools.
 - The MCP client dynamically discovers the tools.

learn-pr/wwl-data-ai/connect-agent-to-mcp-tools/includes/3-mcp-client-server-setup.md

@@ -2,11 +2,11 @@ To dynamically connect tools to your Azure AI Agent, you first need a functionin
 
 ## What is the MCP Server?
 
-The MCP server acts as a registry for tools your agent can use. You can initialize your MCP server using `FastMCP("server-name")`. The FastMCP class uses Python type hints and docstrings to automatically generate tool definitions, making it easy to create and maintain MCP tools. These definitions are then served over HTTP when requested by the client. Because tool definitions live on the server, you can update or add new tools at any time, without having to modify or redeploy your agent.
+The MCP server acts as a registry for tools your agent can use. You can initialize your MCP server using `FastMCP("server-name")`. The FastMCP class uses Python type hints and document strings to automatically generate tool definitions, making it easy to create and maintain MCP tools. These definitions are then served over HTTP when requested by the client. Because tool definitions live on the server, you can update or add new tools at any time, without having to modify or redeploy your agent.
 
 ## What is the MCP Client?
 
-The MCP client acts as a bridge between your MCP server and the Azure AI Agent Service. The client initializes an MCP client session and connets to the server. Afterwards, it performs three key tasks:
+The MCP client acts as a bridge between your MCP server and the Azure AI Agent Service. The client initializes an MCP client session and connects to the server. Afterwards, it performs three key tasks:
 
 - Discovers available tools from the MCP server using `session.list_tools()`.
 - Generates Python function stubs that wrap the tools.