Agents
Agents are used to perform 'fuzzy logic', or perform workflows that require intricate decision making powered by an AI model
Not looking for Agents, and just want to connect to your favorite AI models, like ChatGPT?
Check out this resource instead: Chatbots
Quick Summary
AI agents in Xano refer to autonomous entities designed to perform tasks by leveraging artificial intelligence. Your Xano Agents can integrate with your database, APIs, tasks, and functions, as well as external systems.
These agents can process data, make decisions, and execute actions without human intervention. AI agents in Xano can efficiently handle a variety of applications, from chatbots to data analysis tools, enhancing automation and productivity.
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
Fill out the necessary information
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
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
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.
Creating Tools from Scratch
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.
Build your tool's function stack
If you haven't already, make sure you're familiar with Building with Visual Development
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
Name
Give your agent a name that describes its role or primary function
Customer Support Agent
Description
Internal only field for describing what your agent does
Handles customer inquiries that don't typically need human interaction. Can retrieve user information, update accounts, send verification codes, manage subscriptions, search documentation, and escalate to human support when needed.
Agent Settings
Define dynamic inputs the Agent can accept from Function Stack workflows and reference environment variables
{{ $args.customer_message }}, {{ $args.user_id }}, {{ $args.ticket_priority }}, {{ $env.SUPPORT_API_KEY }}
Model Host
Select the AI model host for the agent
Claude Sonnet 4
Max Steps
Define how many AI requests the Agent can execute to complete a task
8
System Prompt
The core instructions that define your Agent's role, capabilities, and behavior
You are a helpful Customer Support Agent that resolves customer inquiries efficiently. Always verify user identity before making account changes. Use available tools to gather information and resolve issues. If you cannot resolve an issue, create a support ticket for human intervention. Be polite, professional, and solution-oriented.
Prompt
Additional context and instructions sent with each request
Customer inquiry: {{ $args.customer_message }}. User ID: {{ $args.user_id }}. Account status: {{ $args.account_status }}. Please help resolve this customer's issue while following security protocols.
Structured Outputs
Configure your Agent to return responses in JSON format using structured outputs and your predefined schema
✅ Enabled
Output Schema
Define the JSON structure for agent responses
response_message, action_taken, ticket_created, follow_up_required
Tags
Categories for organizing your Agents
customer-service, support, automation
Request History
Controls logging of tool requests
Enabled: Logs requests with options for storage limits
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"
Last updated
Was this helpful?