How to Create a Tool Using GPTBots?

Extending the capabilities of your AI agents requires more than just a large language model; it requires the ability to interact with the world. In this guide, we’ll walk through the process of building a tool with GPTBots step by step.

Tools allow your AI agents to connect with external APIs, fetch real-time data, and execute tasks automatically. By the end of this tutorial, you will know how to configure APIs and authentication to build practical, action-oriented tools for your AI workflows.

Tools within the GPTBots Agent Architecture

The following diagram highlights the role of "Tools" as a critical configuration component for any professional AI Agent.

---
config:
  layout: dagre
  look: handDrawn
---
flowchart TB
    n2["Agent"] --> n6["Configuration"]
    n6 --> n12["LLM"] & n13["Knowledge Base"] & n14["Database"] & n15["Workflows"] & n16["Tools"] & n17["Memory"] & n18["Welcome Guide"] & n19["Human handoff"] & n20["Input / Output"] & n21["Safety Mechanism"]

    n2@{ shape: rect}
    style n2 color:#000000
    style n16 color:#D50000

Step 1: Access the Tools Development Portal

To begin, log in to the GPTBots Portal and locate the "Tools" section in the main navigation menu.

1. Click on "Create Tool" to initiate the setup.
2. A pop-up window will appear requesting your tool’s basic identification details.

Defining Tool Identity

• Tool Name: Choose a clear, concise, and professional name.
• Tool Description: This is a critical SEO and functional step. The description informs the AI’s intent-recognition logic. Be specific about what the tool does and under which specific scenarios the agent should trigger it.

Step 2: Configure Authentication and Security

Once the tool shell is created, you must establish how GPTBots will securely communicate with your external service.

• Choose Authentication Method: Select the standard required by your API (e.g., API Key, OAuth).
• Credential Management: Securely enter your tokens, keys, and identifiers.
• Common Headers: If your APIs share universal headers (e.g., Content-Type: application/json), add them here to streamline the configuration of individual endpoints.

Step 3: Configure API Endpoints

A single GPTBots tool can support multiple API endpoints. The configuration process is broken down into four logical phases:

3.1 Basic API Information

• API Name & Description: Define the specific purpose of this endpoint.
• Method & Path: Select the appropriate HTTP method (GET, POST, PUT, DELETE) and define the endpoint path.
• Note: For dynamic routing, define path parameters using single curly braces (e.g., /user/{id}).

3.2 Input Parameter Definition

Specify every parameter required for a successful API call:

• Name: Must match your API documentation exactly (especially for path parameters).
• Type: Define the data type (string, integer, boolean, etc.).
• Method: Choose whether the parameter resides in the Path or the Query.
• Description: Helps the LLM understand what data to extract from the user conversation to fill this parameter.

3.3 Output Parameters and Data Parsing

• Auto-Parse Feature: Utilize the GPTBots auto-parse tool to generate a list of output fields from a sample response.
• Customize Output: To optimize performance, keep only the essential fields. Reducing "noise" in the output helps the agent process information more accurately without losing core functionality.

3.4 Validation and API Testing

Before deploying, use the built-in Testing Panel:

• Execute a live call to ensure the authentication and parameters are correctly mapped.
• A successful return status confirms your tool is ready for production.

Conclusion

Building custom tools in GPTBots is a streamlined process that bridges the gap between AI reasoning and system execution. By carefully defining your descriptions, authentication, and parameters, you empower your AI agents to interact with the global digital ecosystem with high precision and reliability.