Use AI tools and models in Azure Functions

Azure Functions provides serverless compute resources that integrate with AI and Azure services to streamline building cloud-hosted intelligent applications. This article provides a survey of the breadth of AI-related scenarios, integrations, and other AI resources that you can use in your function apps.

Consider using Azure Functions in your AI-enabled experiences for these scenarios:

Select one of these scenarios to learn more in this article.

This article is language-specific, so make sure you choose your programming language at the top of the page.

Tools and MCP servers

AI models and agents use function calling to request external resources known as tools. Function calling lets models and agents dynamically invoke specific functionality based on the context of a conversation or task.

Functions is particularly well-suited for implementing function calling in agentic workflows because it efficiently scales to handle demand and provides binding extensions that simplify connecting agents with remote Azure services. When you build or host AI tools in Functions, you also get serverless pricing models and platform security features.

The Model Context Protocol (MCP) is the industry standard for interacting with remote servers. It provides a standardized way for AI models and agents to communicate with external systems. An MCP server lets these AI clients efficiently determine the tools and capabilities of an external system.

Azure Functions currently supports exposing your function code by using these types of tools:

Remote MCP servers

Functions supports these options for creating and hosting remote MCP servers:

• Use the MCP binding extension to create and host custom MCP servers as you would any other function app.
• Self host MCP servers created by using the official MCP SDKs. This hosting option is currently in preview.

Here's a comparison of the current MCP server hosting options provided by Functions:

^*Configuration details for self-hosted MCP servers change during the preview.

Queue-based Azure Functions tools

In addition to MCP servers, you can implement AI tools by using Azure Functions with queue-based communication. Azure AI Foundry provides Azure Functions-specific tools that enable asynchronous function calling by using message queues. With these tools, AI agents interact with your code by using messaging patterns.

This tool approach is ideal for AI Foundry scenarios that require:

• Reliable message delivery and processing
• Decoupling between AI agents and function execution
• Built-in retry and error handling capabilities
• Integration with existing Azure messaging infrastructure

Agentic workflows

AI-driven processes often determine how to interact with models and other AI assets. However, some scenarios require a higher level of predictability or well-defined steps. These directed agentic workflows orchestrate separate tasks or interactions that agents must follow.

The Durable Functions extension helps you take advantage of the strengths of Functions to create multistep, long-running operations with built-in fault tolerance. These workflows work well for your directed agentic workflows. For example, a trip planning solution might first gather requirements from the user, search for plan options, obtain user approval, and finally make required bookings. In this scenario, you can build an agent for each step and then coordinate their actions as a workflow using Durable Functions.

For more workflow scenario ideas, see Application patterns in Durable Functions.

Retrieval-augmented generation

Because Functions can handle multiple events from various data sources simultaneously, it's an effective solution for real-time AI scenarios, like RAG systems that require fast data retrieval and processing. Rapid event-driven scaling reduces the latency your customers experience, even in high-demand situations.

Here are some reference samples for RAG-based scenarios:

For RAG, you can use SDKs, including Azure Open AI and Azure SDKs, to build your scenarios. ::: zone-end

AI tools and frameworks for Azure Functions

Functions lets you build apps in your preferred language and use your favorite libraries. Because of this flexibility, you can use a wide range of AI libraries and frameworks in your AI-enabled function apps.

Here are some key Microsoft AI frameworks you should be aware of:

Functions also lets your apps reference third-party libraries and frameworks, so you can use all of your favorite AI tools and libraries in your AI-enabled functions.

Related article

• Azure Functions scenarios