Ext-apps enables developers to embed AI chatbots in external applications using the MCP Apps protocol. Operations teams benefit from standardized UI integration, reducing development time and ensuring consistent user experiences. The protocol connects to MCP servers, allowing for scalable and secure AI chatbot deployment across various platforms.
git clone https://github.com/modelcontextprotocol/ext-apps.githttps://modelcontextprotocol.github.io/ext-apps/api/
["1. Identify the specific tasks you want the AI chatbot to handle in your external application.","2. Ensure your application follows the MCP Apps protocol for seamless integration.","3. Use the prompt template to generate the necessary code or configuration for the integration.","4. Test the integration thoroughly to ensure the chatbot functions as expected and follows the brand guidelines.","5. Deploy the integration and monitor its performance to make any necessary adjustments."]
Create interactive dashboards that visualize real-time data within chat conversations.
Develop forms for user input that can be filled out directly in the chat interface.
Integrate multimedia elements like video players or image galleries into chatbot interactions.
Build tools for data analysis that allow users to manipulate and view data through interactive charts.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/modelcontextprotocol/ext-appsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create an ext-apps integration for [APPLICATION_NAME] to embed an AI chatbot. The chatbot should handle [SPECIFIC_TASKS] and follow the [BRAND_GUIDELINES]. Ensure the integration supports [LANGUAGE] and is compatible with [PLATFORM].
Integration successful! The AI chatbot is now embedded in your [APPLICATION_NAME] application. The chatbot can handle the following tasks: [TASK1], [TASK2], and [TASK3]. It follows the [BRAND_GUIDELINES] and supports [LANGUAGE]. The integration is compatible with [PLATFORM] and is ready for user testing. The chatbot is connected to the MCP servers, ensuring scalable and secure deployment. Users can now interact with the chatbot directly within the application, enhancing their experience and streamlining operations.
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