Update knowledge check YAML and documentation for clarity and accuracy

Author: JulianePadrao

learn-pr/wwl-data-ai/design-implement-sql-solutions-ai-assisted-tools/9-knowledge-check.yml

@@ -9,7 +9,7 @@ metadata:
   author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
-  module_assessment: true
+  module_assessment: false
 azureSandbox: false
 labModal: false
 durationInMinutes: 5

learn-pr/wwl-data-ai/design-implement-sql-solutions-ai-assisted-tools/includes/2-describe-ai-assisted-development-tools.md

@@ -36,7 +36,7 @@ Each Microsoft SQL platform has specific AI integration capabilities:
 
 Model Context Protocol (MCP) extends AI assistant capabilities by allowing them to connect directly to your data sources. When you configure an MCP server for your SQL database, the AI assistant can query your actual schema, sample data, and metadata to provide more accurate and contextual suggestions.
 
-With MCP, your AI assistant isn't just working with generic SQL knowledge—it understands your specific tables, columns, relationships, and data types. This contextual awareness significantly improves the relevance and accuracy of generated code. You'll learn how to [configure MCP tool options](/azure/data-api-builder/mcp/quickstart-visual-studio-code?azure-portal=true) and connect to MCP server endpoints in later units.
+With MCP, your AI assistant isn't just working with generic SQL knowledge—it understands your specific tables, columns, relationships, and data types. This contextual awareness significantly improves the relevance and accuracy of generated code. You'll learn how to [configure MCP tool options](/sql/mcp/?azure-portal=true) and connect to MCP server endpoints in later units.
 
 ## Responsible AI considerations
 

learn-pr/wwl-data-ai/design-implement-sql-solutions-ai-assisted-tools/includes/5-configure-model-mcp-tool-options.md

@@ -5,7 +5,7 @@ Now that you have GitHub Copilot and Fabric Copilot enabled, you can customize h
 GitHub Copilot supports multiple AI models, each with different capabilities and performance characteristics. You can select which model to use for different scenarios based on your needs.
 
 **Available models typically include:**
-- **GPT-4o**: Advanced reasoning capabilities, excellent for complex T-SQL generation and database design questions
+- **GPT**: Advanced reasoning capabilities, excellent for complex T-SQL generation and database design questions
 - **Claude models**: Strong at explaining code and providing detailed documentation
 - **Gemini models**: Available in some configurations with different strengths
 
@@ -64,7 +64,7 @@ When MCP tools are configured, you'll see them listed when you click the tools i
 
 Several MCP server options are available for connecting AI assistants to SQL databases:
 
-**Data API builder MCP**: Connects to SQL Server and Azure SQL databases through Data API builder endpoints. This option provides a secure, managed way to expose database metadata to AI assistants.
+**SQL MCP Server**: Connects to SQL Server and Azure SQL databases using Microsoft's open-source solution built on Data API builder. This option provides a secure, managed way to expose database metadata to AI assistants.
 
 **Microsoft Fabric MCP Server**: Connects to [Fabric data agents as MCP servers](/fabric/data-science/data-agent-mcp-server?azure-portal=true), enabling AI assistants to query lakehouses, warehouses, and SQL databases within Fabric workspaces.
 

learn-pr/wwl-data-ai/design-implement-sql-solutions-ai-assisted-tools/includes/7-connect-mcp-server-endpoints.md

@@ -2,14 +2,14 @@ Model Context Protocol (MCP) servers provide AI assistants with direct access to
 
 ## Connect to SQL Server MCP endpoints
 
-For SQL Server and Azure SQL databases, you can use the Data API builder MCP server or configure direct connections through supported tools.
+For SQL Server and Azure SQL databases, you can use the [SQL MCP Server](/sql/mcp/?azure-portal=true) or configure direct connections through supported tools.
 
-**Using Data API builder:**
+**Using SQL MCP Server:**
 
-Data API builder provides a REST and GraphQL API layer over your database, and it includes MCP support. To set up [SQL MCP servers in VS Code](/azure/data-api-builder/mcp/quickstart-visual-studio-code?azure-portal=true):
+SQL MCP Server is Microsoft's open-source solution built on Data API builder that enables AI agents to interact with SQL databases. To set up [SQL MCP servers in VS Code](/azure/data-api-builder/mcp/quickstart-visual-studio-code?azure-portal=true):
 
-1. Install and configure Data API builder for your database
-2. Enable the MCP endpoint in your Data API builder configuration
+1. Install and configure SQL MCP Server for your database
+2. Enable the MCP endpoint in your SQL MCP Server configuration
 3. Note the MCP endpoint URL (typically ending in `/mcp`)
 4. Add the server to VS Code using the MCP: Add Server command