TW review

Author: Karuna-Mendix

content/en/docs/marketplace/genai/_index.md

@@ -73,7 +73,7 @@ Mendix connectors offer direct support for the following models:
 | -------------- | --------------------- | --------------------- | ------------------- | ----------- | ----------------------- |
 | Mendix Cloud GenAI | Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4.0 Sonnet, Anthropic Claude 4.5 Sonnet | Chat Completions | text, image, document | text | Function calling |
 | | Cohere Embed v3 English and multilangual, Cohere Embed v4 | Embeddings | text | embeddings | |
-| Azure / OpenAI | gpt-4, gpt-4-turbo, gpt-4o, gpt-4o mini, gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-5.0, gpt-5.0-mini, gpt-5.0-nano,  gpt-5.1,  gpt-5.2, o1, o1-mini, o3, o3-mini, o4-mini | Chat completions | text, image, document (OpenAI only) | text | Function calling |
+| Azure / OpenAI | gpt-4, gpt-4-turbo, gpt-4o, gpt-4o mini, gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-5.0, gpt-5.0-mini, gpt-5.0-nano, gpt-5.1, gpt-5.2, o1, o1-mini, o3, o3-mini, o4-mini | Chat completions | text, image, document (OpenAI only) | text | Function calling |
 | | DALL·E 2, DALL·E 3, gpt-image-1 | Image generation | text | image | |
 | | text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large | Embeddings | text | embeddings | |
 | Mistral | Mistral Large 3, Mistral Medium 3.1, Mistral Small 3.2, Ministral 3 (3B, 8B, 14B), Magistral (Small, Medium) | Chat Completions | text, image | text | Function calling |

content/en/docs/marketplace/genai/reference-guide/genai-commons.md

@@ -265,7 +265,7 @@ A tool in the tool collection. This is sent along with the request to expose a l
 | `ToolType` | The type of the tool. Refer to the documentation supplied by your AI provider for information about the supported types. |
 | `Microflow` | The name (string) of the microflow that this tool represents. |
 | `MCPServerName` | The name of the MCP server (only appliable for MCP Tools). |
-| `Schema` | The schema represents the raw JSON schema defined by the tool, usually if the tool is external and not a Mendix microflow. |
+| `Schema` | The schema represents the raw JSON schema defined by the tool. This is typically the case when the tool is external and not a Mendix microflow. |
 
 #### `Function` {#function}
 
@@ -315,7 +315,7 @@ A tool call object may be generated by the model in certain scenarios, such as a
 | `Name` | The name of the tool to call. This refers to the `Name` attribute of one of the [Tools](#tool) in the Request. |
 | `ToolType` | The type of the tool. View AI provider documentation for supported types. |
 | `ToolCallId` | This is a model-generated ID of the proposed tool call. It is used by the model to map an assistant message containing a tool call with the output of the tool call (tool message). |
-| `Input` | The input is the raw tool JSON input generated by the model, usually passed for external tools where no mapping to a microflow needs to happen. |
+| `Input` | The input is the raw tool JSON input generated by the model, usually passed for external tools where no mapping to a microflow is required. |
 
 #### `Argument` {#argument}
 

content/en/docs/marketplace/genai/reference-guide/mcp-modules/mcp-server.md

@@ -62,10 +62,10 @@ The `User` returned in the microflow is used for all subsequent prompt and tool
 
 #### Protocol Version
 
-When creating an MCP server, you need to specify a `ProtocolVersion`. On the official MCP documentation, you can review the differences between the protocol versions in the [changelog](https://modelcontextprotocol.io/specification/2025-03-26/changelog). The latest version of MCP Server module currently only supports `v2025-03-26` and the Streamable HTTP transport. MCP Clients, that need to connect to a Mendix MCP server, should support the same version. Note that Mendix follows the offered capabilities of the MCP Java SDK.
+When creating an MCP server, you need to specify a `ProtocolVersion`. On the official MCP documentation, you can review the differences between the protocol versions in the [changelog](https://modelcontextprotocol.io/specification/2025-03-26/changelog). The latest version of the MCP Server module currently only supports `v2025-03-26` and the Streamable HTTP transport. MCP Clients that need to connect to a Mendix MCP server should support the same version. Note that Mendix follows the offered capabilities of the MCP Java SDK.
 
 {{% alert color="info" %}}
-Since version 4.0.0 of the module the protocol version `v2024-11-05` was replaced by `v2025-03-26` which changed the transport from HTTP + SSE to Streamable HTTP because HTTP + SSE is officially deprecated. Most clients already support the new transport, such as the Mendix [MCP Client](/appstore/modules/genai/mcp-modules/mcp-client/) module.
+Since version 4.0.0 of the module, the protocol version `v2024-11-05` was replaced by `v2025-03-26`, which changed the transport from HTTP + SSE to Streamable HTTP because HTTP + SSE is officially deprecated. Most clients already support the new transport, such as the Mendix [MCP Client](/appstore/modules/genai/mcp-modules/mcp-client/) module.
 {{% /alert %}}
 
 ### Add Tools
@@ -74,7 +74,7 @@ After the [Create MCP Server](#create-server) action, you can add one or multipl
 
 The selected microflow must adhere to the following principles:
 
-* Input needs to be the same as described in the `Schema` attribute (only primitives and/or an object of type `MCPServer.Tool` are supported). If no Schema is passed in the `Add tool` action, it will be automatically created based on the microflow's input parameters, setting all of them as required.
+* Input needs to be the same as described in the `Schema` attribute (only primitives and/or an object of type `MCPServer.Tool` are supported). If no Schema is passed in the `Add tool` action, it will be automatically created based on the microflow's input parameters, by setting all of them as required.
 * The return value must be either of type `String` or `TextContent`. You can create a `TextContent` object within the microflow to return the relevant information to the model based on the outcome of the microflow.
 
 For an example, see the `Example Implementations` folder inside of the module.