Kuika's AI Agents feature allows you to integrate more interactive and scenario-based artificial intelligence experiences into your applications. With this feature, you can create artificial intelligence agents that perform different tasks, have specific roles, and can provide dynamic responses based on user input.
Steps to Create an AI Agent
Log in to the Kuika platform and open the project you want to work on.
Go to the Datasources module.
Go to the “AI Agents” section in the left panel.
Click the + icon to create a new AI Agent.
In the window that opens, you will need to fill in the following information:
Agent Name
Give the agent a descriptive name (for example, “JobPostGeneratorAgent”).
Model Selection
There are two different model types available:
All: Used for versatile, general-purpose tasks.
CrewAI: Provides an advanced scenario infrastructure that enables multiple AI agents to work as a team.
In the AI Agent Chat screen, you can move to a new line using the Shift + Enter combination. This allows you to more easily create multi-line messages or enter inputs in a bullet-style format.
AI Agent Templates
You can create an agent using ready-made templates or define a structure from scratch using the Custom option:
Custom
Definition: Allows you to create your own agent from scratch.
Use Case: For developers who want to use unique task definitions, custom user inputs, or different AI models.
Features: You have full control over role prompts, user prompts, models, and parameters.
Sample Input: “Generate a title and description for a podcast episode.”
Employee Researcher
Definition: Gather information about a specific employee from the internet or a database.
Use Case: Human resources, internal communications, and executive dashboards.
Data Source: Typically supported by Serper Tool.
Input: Employee name, position, email.
Output: Structured text or JSON about the employee's history, competencies, and projects.
Company Researcher
Description: Conducts online research on a specified company and provides summary information.
AI Agents can be adapted to different scenarios with their customizable template structure. The system offers a flexible solution thanks to input definitions, user interaction, and background tools.
How to Use?
Define Agent Inputs:
Click the “Agent Inputs” button in the upper right corner.
Define the required inputs according to their types:
String: Text information (e.g., candidate name, product name)
Boolean: True/False options (e.g., was the reference check performed?)
Integer: Whole numbers (e.g., years of experience)
Float: Decimal numbers (e.g., expected salary)
Interact with the Chatbot:
The inputs you defined become active in the chatbot interface.
The user enters data into the Chatbot using natural language.
Sample message:
“Candidate name: Ayşe Demir, Was the reference check performed? Yes, Years of experience: 6, Expected salary: 85000.”
AI Agent Generates Response:
Creates an automatic response based on the defined inputs.
If necessary, analysis, calculation, or data query operations are performed.
Results are presented to the user in real time.
Perform Actions Using Tools:
Thanks to the tools you add to the Agent, you can create files, extract data, and perform analysis.
Example Scenario: Candidate Evaluation
Objective: Obtain candidate information, perform suitability assessment, and save the result to a file.
Steps:
Define the following inputs from Agent Inputs:
candidateName (String)
hasReferenceChecked (Boolean)
yearsOfExperience (Integer)
expectedSalary (Float)
Write to the chatbot as follows:
“Candidate name: John Doe, Has the reference check been completed? Yes, Years of experience: 6, Expected salary: 85,000.”
The agent generates the following response:
John Doe
Reference check completed.
With 6 years of experience, he is suitable for the position.
Expected salary: 85,000 TL – This value appears to be in line with the market average.
Evaluation report is being generated..."
FileWriterTool is activated and creates a file named john_doe_evaluation.txt.
What is Agent Response Builder?
It is used to configure what kind of response the agent will give to the user. It enables AI responses to be generated in a dynamic, meaningful, and structured way. This structure allows you to:
Write custom messages based on inputs,
Embed tool outputs into the response,
Generate flexible content with conditional statements (e.g., show if reference check is done, warn if not).
It can be accessed by clicking the view icon (Response) in the Agent panel.
Here, you can call all inputs using the input name in the text and define conditional statements with Jinja-like structures.
Supported Tool Descriptions
Settings for MCP-based integrations (Brave Search, Slack, Github, GoogleWorkspace, GoogleMaps, Youtube, Trello, Airbnb, Office365, Dropbox) are configured through the Configuration Manager module. Once API keys, access permissions, and connection details for the relevant MCP are defined in this module, they become available for use within the AI Agent.
Project & Management
Trello Boards
Purpose: Access Trello boards and perform actions on cards.
Usage: Tasks on boards can be read, and card details can be retrieved.
Example Usages:
List all cards on a board
Get information about a specific task
Jira Tasks
Purpose: Manage tasks and tickets on Jira.
Usage: Issues can be listed and their details can be reviewed.
Example Uses:
List open tickets
Check the status of an issue
File & Storage
Dropbox Files
Purpose: Access Dropbox files.
Usage: Files can be listed and their contents can be read.
Google Workspace
Purpose: Work with Google Drive, Docs, and Sheets documents.
Usage: Documents can be opened and searched.
Open File
Purpose: Open uploaded files.
Save File
Purpose: Save created content as a file.
Read Excel
Purpose: Read and analyze Excel files.
Example Uses:
Analyze sales reports
Make list comparisons
Collaboration & Communication
Slack Messages
Purpose: Get data from Slack channels.
Usage:
Read messages
Summarize conversations
Github Repos
Purpose: Review repositories and commits.
Usage:
View recent changes
Follow up on open issues
YouTube Content
Purpose: Access YouTube videos.
Usage:
Search for videos
Get description information
Airbnb Data
Purpose: Get accommodation information via Airbnb.
Usage:
Search by date
Filter by price
Office365
Purpose: Integration with Outlook, OneDrive, and Office documents.
Usage:
Read emails
Perform file analysis
Data & Analytics
Web Scraper Tool
Purpose: Extract data from static websites.
Dynamic Website Scraper (Firecrawl MCP)
Purpose: Crawl dynamic websites.
Code Runner
Purpose: Run and analyze Python code.
Serper Dev Tool
Purpose: Perform web searches via Google.
Search & Maps
Web Search (Brave)
Purpose: Perform searches on the internet.
Google Maps
Purpose: Obtain location and venue information.
Tips
Any changes made to inputs automatically update the AI response.
Tool combinations allow you to create different usage scenarios.
Each input defined in the prompt can be used directly as {{inputName}}.
How to Configure Serper Tool Settings?
1. Add Configuration to the Application
Log in to the Kuika platform.
Open the project you will be working on from the Apps screen.
Click on the Configuration Manager module.
On the screen that opens, give the configuration a name and click the CREATE button.
2. Configure Serper Tool Settings
After creating a new configuration, open the App Settings screen.
Go to the AI Settings section.
Click on the Serper Tool option from the drop-down menu.
Click the ADD NEW button.
Configure the following settings in the pop-up window that opens:
Name: Name to be given to the configuration.
API Key: Access key obtained via the Serper API.
Once the Serper Tool becomes available for use by the Agent, it is automatically detected in AI Agent configurations and actively used in tasks involving external data sources.
Using the AI Agent
Go to the UI Design module.
Open the screen where you want to add the Agent.
Click on the +ADD ACTION > AI Agents tab and select the agent you created.
Connect the relevant user inputs and activate the AI-powered scenarios.
