📄️ 01 - Build your first conversational agentic workflow in Azure Logic Apps
Learn how to build a conversational agentic workflow in Azure Logic Apps, connect it to an Azure OpenAI model, and add its first tool.
📄️ 02 - Debug your conversational agentic workflow in Azure Logic Apps
Learn how to monitor and debug a Logic Apps conversational agentic workflow using run history, chat transcripts, tool calls, and model inputs/outputs.
📄️ 03 - Connect tools to external services
Learn how to connect a conversational agent workflow in Azure Logic Apps to external services by using connectors and how to expose connector actions as tools for models, agents, and MCP clients to use.
📄️ 04 - Add user context to tools
Learn how to set up on-behalf-of (OBO) authorization for your tools. Learn how to run connector actions with a signed-in user identity by using OBO authorization in conversational agent workflows for Azure Logic Apps.
📄️ 05 - Connect your agentic workflows with A2A protocol
Learn how to integrate Azure Logic Apps conversational agentic workflows with external services using the A2A protocol and the A2A Python SDK.
📄️ 06 - Deploy your agentic workflows and clients
Learn how to deploy Logic Apps conversational agentic workflows and built-in chat client, configure authentication and developer identity, and link to existing Logic Apps deployment workflows.
📄️ 07 - Deploy your agentic workflows to Microsoft Teams
Learn how to deploy Logic Apps conversational agentic workflows to Microsoft Teams to enable interacting with agentic workflows through the Teams chat.