This project demonstrates how to utilize the MCP protocol with Azure OpenAI, providing tools and components to interact with language models seamlessly within Azure Container Apps environment.
Added on:
Created by:
Apr 25 2025
This project demonstrates how to utilize the MCP protocol with Azure OpenAI, providing tools and components to interact with language models seamlessly within Azure Container Apps environment.
Added on:
Created by:
Apr 25 2025
Wassim Chegham
Featured
What is Azure Container Apps - AI & MCP Playground?
This MCP implementation includes a host, client, server, and tools to facilitate communication with various LLM providers like Azure OpenAI, OpenAI, and GitHub Models. It offers a demo terminal for interacting with a TODO list agent, equipped with features like resource management, prompts, sampling, and tools execution. The system supports multiple MCP server protocols (HTTP and SSE), allowing flexible deployment options and integration with cloud-based AI services. It enhances development and testing of AI-driven applications in Azure, streamlining model interaction, tool utilization, and data management within a containerized environment.
Who will use Azure Container Apps - AI & MCP Playground?
- Developers integrating MCP with Azure AI services
- AI application developers
- Cloud solution architects
- DevOps engineers working with containerized AI solutions
How to use the Azure Container Apps - AI & MCP Playground?
- Step 1: Clone the repository
- Step 2: Install dependencies with npm
- Step 3: Configure environment variables for your LLM provider
- Step 4: Run the MCP servers (HTTP and SSE) using Docker or npm
- Step 5: Launch the MCP host application
- Step 6: Interact with the AI agent via the terminal or API
Azure Container Apps - AI & MCP Playground's Core Features & Benefits
The Core Features
- MCP Host interaction
- MCP Client communication
- HTTP and SSE MCP server implementation
- Tool integration for resource management, prompts, and sampling
- Support for Azure OpenAI, OpenAI, GitHub Models APIs
The Benefits
- Seamless integration with Azure and other LLM providers
- Flexible deployment with Docker or in DevContainer
- Supports multiple communication protocols
- Enables AI-driven automation within Azure Container Apps
- Modular and extensible architecture
Azure Container Apps - AI & MCP Playground's Main Use Cases & Applications
- AI assistant or chatbot integration
- Automated resource and task management
- Development and testing of MCP-based AI workflows
- AI model experimentation within Azure environment
FAQs of Azure Container Apps - AI & MCP Playground
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