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Custom Tools allow you to connect any HTTP REST API to your voice agent. When a user asks a question or makes a request that requires external data or an action, the agent automatically calls your configured API and delivers the result — all in real time.

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How Tool Calling Works

When a tool is configured, the AI agent automatically detects when it’s needed during a conversation:
  1. User asks a question that requires an external action (e.g., “What’s the EMI for a ₹3,00,000 course?”)
  2. Agent generates a tool call request with the extracted parameters.
  3. Platform executes the API call asynchronously in the background.
  4. Result is returned to the agent, which responds to the user with the information.
Tool execution is non-blocking. The agent continues listening and can respond to follow-up questions while the API call is in progress. Results are delivered automatically as soon as they arrive.

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Best Practice: Test in Postman First

Before adding a custom tool, always test the API in Postman first:
  • If you’ve received a cURL command, paste it into Postman and test with multiple scenarios.
  • Verify response formats, error cases, and parameter requirements.
  • Identify which values are static (e.g., API keys) vs. dynamic (e.g., user-provided inputs).
This ensures the API works correctly before you integrate it into your agent.

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Configuring a Custom Tool

Navigate to your agent → Knowledgebase and Tools → Custom Tools → New Tool. Below is a step-by-step walkthrough using an EMI Calculation API as an example.

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Step 1: Basic Information

Fill in the top section of the form:
Custom tool basic info
You can also use the Import from cURL feature to auto-populate these fields from a cURL command. Always verify the imported values after importing.

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Step 2: Headers

Switch to the Headers tab to add any HTTP headers required by the API. Click + Add header and enter the header name and value. For our example: Headers can contain:
  • Static values — Fixed strings like application/json or Bearer your-api-key
  • Dynamic values — Use {variable_name} syntax to inject runtime values
Custom tool headers configuration

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Step 3: Request Body

Switch to the Body tab to configure the request payload.
  1. Select Body Type: Choose Raw (JSON) for JSON payloads or Form Data for form-encoded data.
  2. Enter the Request Body with {variable_name} placeholders for dynamic values:
The {course_fee} placeholder tells the system to inject the value extracted from the user’s conversation at runtime.
Custom tool body configuration

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Step 4: Variables

Switch to the Variables tab. Click Refresh Variables to auto-detect all {variable_name} placeholders used in your headers, parameters, or body. For each detected variable, configure:
Custom tool variables configuration
If a variable name already exists in your system prompt (e.g., from lead data), it will be treated as a lead variable and won’t appear here. Only variables that the agent needs to extract at runtime from the conversation are listed.

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Step 5: Save the Tool

Once all fields are configured, click Add tool. The tool will be attached to your agent and can be referenced by the tool name you specified (e.g., emi_calculation).

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Static vs Dynamic Values

Understanding the difference is key to configuring tools correctly:

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Tips for Writing Good Descriptions

  • Tool description: Clearly state what the tool does and when to use it. Example: “Calculates EMI details for a given course fee. Use when the user asks about payment plans or EMI options.”
  • Variable description: Specify what to extract and the expected format. Example: “The appointment date in YYYY-MM-DD format.”
  • Keep descriptions concise — 1-2 sentences maximum.
💡 Tip After adding the tool, make a test call to your agent to verify the tool is triggered correctly and returns the expected results.