Agents

Introduction to AI Agents

Tools for Agents & MCP Servers

What are Agents?

AI agents in Xano serve as integral components for building intelligent, automated systems as a part of your backend. These agents are designed to function autonomously, interacting with various elements of your app such as your APIs and database, as well as external systems, to streamline operations and enhance efficiency. AI agents can intelligently interpret inputs, process data, and deliver actionable outputs, all without the need for continuous human oversight.

Agents in Xano can leverage any of the most popular AI models once you provide an API key, such as:

• OpenAI

• Grok

• Anthropic / Claude

• Google Gemini

You can leverage the same visual builder you're used to using today to create workflows and functions that enable the agents to interact seamlessly with databases and external systems. With these foundational elements in place, AI agents can execute complex tasks, perform data analysis, or even serve as intelligent chatbots, making them versatile tools for a wide range of applications.

Building Agents in Xano

1

From the left-hand navigation, click AI, then Agents

2

Click + Add Agent

3

Fill out the necessary information

Note

Please note that not all models support certain features such as:

• Structured outputs

• Reasoning

• Tool calls

In addition, some models may support individual features, but not combinations of features, such as:

• Structured outputs with tool calls

• Tool calls with reasoning

This is not an issue with Xano or with your agent builds — this is dictated by the model you're using. If you encounter errors when testing your Agents, try using a different model and check to make sure that your model supports the feature(s) you have enabled, especially if you are using more than one of these features together.

Parameter Name

Purpose

Example

Name

Give your agent a name that describes its role or primary function

Order Processing Agent

Description

Internal only field for describing what your agent does

Analyzes incoming orders, decides on fulfillment priority, and triggers shipping workflows

Agent Settings

Define dynamic inputs the Agent can accept from Function Stack workflows and reference environment variables

Configure placeholders with {{ $args.propertyName }} for workflow inputs, and {{ $env.variableName }} for environment variables

Model Host

Select the AI model host for the agent

Anthropic (Claude) OpenAI Google Gemini

Max Steps

Define how many steps the Agent can execute to complete its task.

5

System Prompt

The core instructions that define your Agent's role, capabilities, and behavior

You are a helpful AI Agent that completes tasks accurately. When you need additional information to complete a task, use the available tools. Never make assumptions.

Prompt

Additional context and instructions sent with each request

Please help the customer with their inquiry: {{ $args.customer_message }}. Their account ID is {{ $args.account_id }}.

Structured Outputs

Configure your Agent to return responses in a specific JSON format using structured outputs and your predefined schema

Checkbox to enable/disable

Output Schema

Define the JSON structure for structured outputs

text, user_email

Tags

Categories for organizing your Agents

contact, messaging

Request History

Controls logging of requests toRequest History

Inherit Settings: Uses workspace logging settings

Disabled: No logs recorded

Enabled: Logs requests with options for storage limits

4

Add some tools to your Agent

An Agent needs tools to function — the tools are essentially single functions that the Agent can perform, such as looking up user data or cancelling a subscription.

Using Existing Function Stacks as Tools

1

In the existing function stack, click the ⋮ settings icon in the upper-right corner of another function stack, and click Use As AI Tool

2

Choose the Agent or MCP Server you'd like to add the tool to, and give it a name. This name is what the command will be, so make sure it's understandable

3

A new tool will be created in your chosen destination with a function to call the function stack

Xano will not make a copy of your existing function stack; instead, it will use a Run Endpoint function and call that function stack internally. This is ideal, so you only have to maintain one function stack.

4

Head to your tool's settings and add instructions

Instructions are important to have so the AI models and clients interacting with this tool understand how to use it.

Creating Tools from Scratch

1

From the left-hand navigation menu, click Tools, then + Add Tool

2

Fill out the required information

• Name

  • Give your tool a recognizable name. This is also the command that will be used to execute your tool.

• Description

  • This is an internal-only field just for you to describe the purpose of the tool.

• Allow Connections

  • Enable or diffsable connection to this specific tool

• Add Tag

  • Tag your tools for easier search across your Xano workspace

• Authentication

  • Determine if this tool requires an authentication token

• Tool Instructions

  • These instructions are what your clients will use to understand how to send requests to the tool, and what the expected result will be. Markdown format is recommended.

3

Build your tool's function stack

If you haven't already, make sure you're familiar with Building with Visual Development

4

Add the tool to an Agent or MCP Server

From the Agent or MCP Server, choose + Add Tool and select the tool you just created.

Structured Outputs

Structured Outputs are used for providing a specific format that you need your agent to return its result as. This is especially useful when you are calling agents from other agents and want to ensure that the output from Agent 1 is clear and easy to understand for Agent 2.

You can add structured outputs to your Agent in the settings by checking the Structured Outputs checkbox, and then clicking + Add Output Schema to build your output schema.

Example Agents

🤖 Customer Support Agent

Purpose

This Agent is designed to handle customer inquiries that don't typically need human interaction.

Tools

An Agent designed for this purpose might have the following tools available:

• Get User Information

  • Retrieves user information from the database

• Update User Information

  • Retrieves existing user information from the database, and updates it per a user's request, such as changing their phone number or address

• Send Verification Code

  • This tool could be used as a secondary security measure to verify that the request is coming from the user that the data belongs to

• Change Subscription

  • Based on the user's request, this could be used to stop an upcoming renewal, or cancel a subscription immediately. Because Agents excel at 'fuzzy logic' depending on certain circumstances, this could also be used for things like churn prevention — dynamically offering the user a discount to stay, for example

• Search Documentation

  • Calls an external API from your chosen documentation platform to search your product documentation in an attempt to solve the user's query without human intervention

• Create Support Ticket

  • In the case that the Agent does not have the necessary tools to solve the user's concerns, create a support ticket for human intervention

Agent Configuration

Example Interaction Flowcharts

1. Account Information Request

"What's my current subscription plan?"

2. Address Change Request

"I need to update my shipping address"

3. Billing Question

"Why was I charged twice this month?"

4. Technical Issue

"The app keeps crashing on my phone"