Welcome to Day 3 of the Azure AI Foundry Agent Webinar Series! Today, you'll learn about MCP (Model Context Protocol) prebuilt servers, how they simplify agent deployment, and how to use them in real-world scenarios.
By the end of Day 3, you will:
- Understand what MCP (Model Context Protocol) is and why it matters
- Explore prebuilt MCP servers and their use cases
- Learn how to deploy and connect agents to MCP servers
- Get hands-on with a deployment workflow
MCP (Model Context Protocol) is a standard for connecting AI agents and applications to a variety of models and tools, enabling flexible, modular, and scalable AI solutions.
- Prebuilt MCP servers provide ready-to-use endpoints for common AI tasks (e.g., retrieval, summarization, Q&A)
- They allow you to quickly integrate advanced capabilities into your agents without building everything from scratch
For a deep dive into MCP architecture and concepts, see mcp.md.
- Explore available MCP servers in Azure AI Foundry or via the MCP Servers GitHub
- Connect your agent to a prebuilt server using the Azure AI Foundry portal or SDK
- Test your agent with the new capabilities (e.g., retrieval-augmented generation, document Q&A)
For a step-by-step guide, see the MCP for Beginners repository
| Directory | Description | Client/Server | Navigation |
|---|---|---|---|
code/ |
Live AI agent system: GitHub profile analysis, project ideation, and event recommendations | Both | README |
simple-mcp/ |
Minimal MCP server and client example | Both | README |
web-search-mcp/ |
MCP server/client for web search integration | Both | README |
Each subdirectory contains its own README with setup and usage instructions for the respective MCP code sample.
- Select a prebuilt MCP server (e.g., retrieval, summarization)
- Configure your agent to use the MCP endpoint
- Deploy and test the agent in the playground
- Monitor and iterate as needed
- MCP for Beginners (GitHub)
- MCP Servers (GitHub)
- MCP Introduction (Official Site)
- MCP Architecture and Concepts
Here are some recent contributions and related work you may find useful:
- web-search-mcp (Advanced Topics)
- HTTP Streaming Solution (Python)
- Practical Implementation Samples (Python)
- Case Study Scenarios 3, 4, 5
- GitHub MCP Sample
Navigate to the code samples above for hands-on practice, and use the resources to deepen your understanding of MCP and agent deployment!