Static tool registration works fine until your agent needs access to a growing, changing set of capabilities - that's where MCP (Model Context Protocol) changes the game.

This talk is a code-level dive into connecting MCP-hosted tools to Azure AI agents built on Microsoft Foundry:
- how the MCP server/client model handles tool discovery and invocation
- how to wrap MCP tools as async functions and register them with an agent
- how to build an agent that dynamically discovers and calls tools at runtime instead of at build time.

I'll walk through the actual plumbing - client-server handshake, async function wrapping, and the failure modes that show up when tool discovery happens dynamically (timeouts, schema mismatches, tools disappearing mid-session) - and share debugging techniques for when an agent picks the wrong tool or fails to invoke one correctly.