This MCP project demonstrates how to use the MCP protocol with Azure OpenAI, providing a simple interface to interact with OpenAI's API through MCP server and client components, enabling efficient AI application development.
Added on:
Created by:
May 12 2025
This MCP project demonstrates how to use the MCP protocol with Azure OpenAI, providing a simple interface to interact with OpenAI's API through MCP server and client components, enabling efficient AI application development.
Added on:
Created by:
May 12 2025
Azure Samples
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What is Azure Container Apps - AI & MCP Playground?
This project illustrates how to implement the MCP protocol with Azure OpenAI, enabling seamless communication between MCP host, client, and server components. It provides a terminal-based demo where users can interact with an AI agent that accesses tools like a TODO list, with the backend handling requests using either HTTP or SSE MCP server implementations. It supports multiple language models such as Azure OpenAI, OpenAI, and GitHub models, with configuration options for API keys, endpoints, and Docker or local deployment methods for testing and development. The setup includes a Postgres database for state management and various tools for AI-driven interactions, making it ideal for building scalable AI-enabled applications in the cloud.
Who will use Azure Container Apps - AI & MCP Playground?
- Developers interested in MCP and AI integration
- AI application developers using Azure OpenAI
- Cloud solution architects implementing scalable AI systems
How to use the Azure Container Apps - AI & MCP Playground?
- Step 1: Clone the repository from GitHub.
- Step 2: Install dependencies using npm for MCP host and servers.
- Step 3: Configure environment variables with your Azure/OpenAI/GitHub API keys.
- Step 4: Run MCP servers locally via Docker or directly with npm commands.
- Step 5: Launch the MCP host to interact with the AI agent through terminal commands.
- Step 6: Use the provided tools to add, list, complete, or delete TODO items via the interface.
Azure Container Apps - AI & MCP Playground's Core Features & Benefits
The Core Features
- Interaction with OpenAI, Azure OpenAI, GitHub AI models
- Supports HTTP and SSE protocols for MCP communication
- Tools for managing TODO lists (add, list, complete, delete)
- Configurable environment for deployment via Docker or local setup
The Benefits
- Enables scalable AI integrations across cloud environments
- Supports multiple protocol and model configurations
- Streamlined setup for development and testing
- Flexible architecture with database support for state management
Azure Container Apps - AI & MCP Playground's Main Use Cases & Applications
- Building AI-powered chatbots and agents
- Automating workflows with AI tools in cloud environments
- Integrating MCP with Azure OpenAI for enterprise solutions
- Developing scalable AI services for customer support and knowledge management
FAQs of Azure Container Apps - AI & MCP Playground
Developer
- Azure-Samples
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