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

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| [Blank GenAI App](https://marketplace.mendix.com/link/component/227934) | Start from scratch to create a new application with GenAI capabilities and without any dependencies. | Starter App | 10.24 |
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| [Conversational UI](/appstore/modules/genai/conversational-ui/) | Create a Conversational UI or monitor token consumption in your app. | UI Module | 10.24 |
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| [GenAI Commons](/appstore/modules/genai/commons/) | Common capabilities that allow all GenAI connectors to be integrated with the other modules. You can also implement your own connector based on this. | Common Module | 10.24 |
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| [GenAI Showcase App](https://marketplace.mendix.com/link/component/220475) | Understand what you can build with generative AI. Understand how to implement the Mendix Cloud GenAI, OpenAI, and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. |Showcase App | 10.24 |
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| [GenAI Showcase App](https://marketplace.mendix.com/link/component/220475) | Understand what you can build with generative AI. Understand how to implement the Mendix Cloud GenAI, OpenAI, and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. | Showcase App | 10.24 |
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| [MCP Client](/appstore/modules/genai/mcp-modules/mcp-client/) | Access tools and prompts available via MCP (Model Context Protocol) inside of your Mendix app and add them to LLM requests. | Connector Module | 10.24 |
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| [MCP Server](/appstore/modules/genai/mcp-modules/mcp-server/) | Make your Mendix business logic available to any agent in your enterprise landscape with the Mendix MCP Server module. Expose reusable prompts, including the ability to use prompt parameters. List and run actions implemented in the application as a tool. | Module | 10.24 |
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| [Mendix Cloud GenAI Connector](/appstore/modules/genai/mx-cloud-genai/MxGenAI-connector/) | Connect to Mendix Cloud and utilize Mendix Cloud GenAI resource packs directly within your Mendix application. | Connector Module | 10.24 |
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Mendix connectors offer direct support for the following models:
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| Architecture | Models | Category | Input | Output | Additional capabilities |
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|--------------|---------------------|---------------------|-------------------|-----------|-------------------------|
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| -------------- | --------------------- | --------------------- | ------------------- | ----------- | ----------------------- |
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| Mendix Cloud GenAI | Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4.0 Sonnet | Chat Completions | text, image, document | text | Function calling |
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| | Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | |
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| 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 | Chat completions | text, image, document (OpenAI only) | text | Function calling |
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| | DALL·E 2, DALL·E 3, gpt-image-1 | Image generation | text | image | |
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| | text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large | Embeddings | text | embeddings| |
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| | text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large | Embeddings | text | embeddings | |
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| 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 |
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| | Codestral, Devstral (Small, Medium), Open Mistral 7B, Mistral Nemo 12B | Chat Completions | text | text | Function calling |
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| | Mistral Embed, Codestral Embed | Embeddings | text | embeddings | |
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| Amazon Bedrock | Amazon Titan Text G1 - Express, Amazon Titan Text G1 - Lite, Amazon Titan Text G1 - Premier | Chat Completions | text, document (except Titan Premier) | text | |
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| | AI21 Jamba-Instruct | Chat Completions | text | text | |
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| | AI21 Labs Jurassic-2 (Text) | Chat Completions | text | text | |
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| | AI21 Jamba-Instruct | Chat Completions | text | text | |
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| | AI21 Labs Jurassic-2 (Text) | Chat Completions | text | text | |
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| | Amazon Nova Pro, Amazon Nova Lite | Chat Completions | text, image, document | text | Function calling |
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| | Amazon Titan Image Generator G1 | Image generation | text | image | |
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| | Amazon Titan Embeddings Text v2 | Embeddings | text | embeddings| |
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| | Anthropic Claude 2.0, Anthropic Claude 2.1| Chat Completions | text, document | text | |
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| | Anthropic Claude 3 Sonnet, Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.5 Sonnet v2, Anthropic Claude 3 Haiku, Anthropic Claude 3 Opus, Anthropic Claude 3.5 Haiku, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4 Sonnet | Chat Completions | text, image, document | text | Function calling |
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| | Amazon Titan Embeddings Text v2 | Embeddings | text | embeddings | |
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| | Anthropic Claude 2.0, Anthropic Claude 2.1 | Chat Completions | text, document | text | |
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| | Anthropic Claude 3 Sonnet, Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.5 Sonnet v2, Anthropic Claude 3 Haiku, Anthropic Claude 3 Opus, Anthropic Claude 3.5 Haiku, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4 Sonnet | Chat Completions | text, image, document | text | Function calling |
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| | Cohere Command | Chat Completions | text, document | text | |
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| | Cohere Command Light | Chat Completions | text | text | |
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| | Cohere Command R, Cohere Command R+ | Chat Completions | text, document | text | Function calling |
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| | Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | |
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| | DeepSeek, DeepSeek-R1 | Text | text | document | |
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| | Meta Llama 2, MetaLlama 3| Chat Completions | text, document | text | |
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| | Meta Llama 3.1| Chat Completions | text, document | text | Function calling |
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| | Meta Llama 2, MetaLlama 3 | Chat Completions | text, document | text | |
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| | Meta Llama 3.1 | Chat Completions | text, document | text | Function calling |
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| | Mistral AI Instruct | Chat Completions | text, document | text | |
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| | Mistral Large, Mistral Large 2 | Chat Completions | text, document | text | Function calling |
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| | Mistral Small | Chat Completions | text | text | Function calling |
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| | OpenAI gpt-oss-20B, gpt-oss-120b | Chat Completions | text | text | |
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| | OpenAI gpt-oss-20B, gpt-oss-120b | Chat Completions | text | text | |
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For more details on limitations and supported model capabilities for the Bedrock Converse API used in the ChatCompletions operations, see [Supported models and model features](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-supported-models-features.html) in the AWS documentation.
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‎content/en/docs/marketplace/genai/mendix-cloud-genai/navigate_mxgenai.md‎

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{{% alert color="info" %}}
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Ensure you are using Mendix Cloud GenAI Connector version 5.3.0 to support the latest Cohere Embed v4 model. Also, note that model changes will be reflected in the keys inside of your Mendix Cloud GenAI powered application from Mendix Cloud GenAI Connector version 5.4.0 only.
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Ensure you are using Mendix Cloud GenAI Connector version 5.3.0 and above to support the latest Cohere Embed v4 model. To see the upgraded model version reflected in your GenAI Connector after upgrading, make sure you are using Mendix Cloud GenAI Connector version 5.4.0 and above.
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### Team

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

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### Limitations {#limitations}
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The current version has the following limitations:
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* Tools and prompt messages can only return String content.
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The current version has the following limitation: Tools and prompt messages can only return String content.
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{{% alert color="info" %}}
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Note that the MCP Client module is still in its early version, and newer versions may include breaking changes. Since both the open-source protocol and the Java SDK are still evolving and regularly updated, these changes may also affect this module.
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#### Protocol Version
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When creating an MCP client, 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 MCP Client module currently supports `v2024-11-05` with the HTTP+SSE transport and `v2025-03-26` with the Streamable HTTP transport, which is the new standard method. MCP servers should support the same version as the client. Note that Mendix supports the capabilities provided by the MCP Java SDK.
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When creating an MCP client, 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 MCP Client module currently supports `v2024-11-05` with the HTTP+SSE transport and `v2025-03-26` with the streamable HTTP transport, which is the new standard method. MCP servers should support the same version as the client. Note that Mendix supports the capabilities provided by the MCP Java SDK.
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### Discovering Resources {#discover-resources}
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‎content/en/docs/marketplace/genai/reference-guide/mcp-modules/mcp-server.md‎

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* Tools can only return String values, either directly as String type or using the `TextContent` entity.
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* Prompts can only return a single message.
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* Running an MCP Server is currently only supported on single-instance environments.
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* For HTTP+SSE transport (protocol version `v2024-11-05`), tool execution with large payloads are not returned successfully
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* For HTTP+SSE transport (protocol version `v2024-11-05`), tool execution with large payloads are not returned successfully.
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Note that the MCP Server module is still in its early version and latest versions may include breaking changes. Since both the open-source protocol and the Java SDK are still evolving and regularly updated, these changes may also affect this module.
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### Create MCP Server {#create-server}
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The `Create MCP Server` action initializes an MCP server in the Mendix runtime, creates and returns the `MCPServer` object. You can use the created `MCPServer` to add tools or prompts. The `Path` attribute determines how external systems can reach the MCP server, that means this value needs to be known to the the MCP Client (usually set in a configuration file). After the action gets triggered, the server becomes available for external clients to connect. Note that the path cannot be `sse` nor `mcp` and cannot end on `/sse` nor `/mcp`, because those are reserved endpoints.
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The `Create MCP Server` action initializes an MCP server in the Mendix runtime, creates and returns the `MCPServer` object. You can use the created `MCPServer` to add tools or prompts. The `Path` attribute determines how external systems can reach the MCP server, that means this value needs to be known to the the MCP Client (usually set in a configuration file). After the action gets triggered, the server becomes available for external clients to connect. Note that the path must not be `sse` or `mcp`, and must not end with `/sse`or `/mcp`, as these are reserved endpoints.
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Based on your use case, this action can be triggered manually by an admin if wrapped around a microflow accessible in the UI, via an after start-up microflow, or by any other microflow such as a scheduled event.
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#### Protocol Version
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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 MCP Server module currently only supports `v2024-11-05` with the HTTP+SSE transport and `v2025-03-25` with the Streamable HTTP transport, which is the new standard 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.
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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 MCP Server module currently only supports `v2024-11-05` with the HTTP+SSE transport and `v2025-03-25` with the streamable HTTP transport, which is the new standard 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.
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### Add Tools
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{{% alert color="warning" %}}
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Function / tool calling is a highly effective capability and should be used with caution.
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Function/tool calling is a highly effective capability and should be used with caution.
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Mendix strongly recommends keeping the user in the loop (such as by using confirmation logic which is integrated into many MCP clients), if the tool microflows have a potential impact on the real world on behalf of the end-user. Examples include sending emails, posting content online, or making purchases. In such cases, evaluate the use cases and implement security measures when exposing these tools to external AI systems via MCP.
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