> For the complete documentation index, see [llms.txt](https://university.mindstudio.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://university.mindstudio.ai/deployment-of-ai-agents/webhook-triggered.md).

# Webhook-Triggered

## Overview

Webhook-triggered Agents allow you to initiate an AI workflow via a simple HTTP POST request to a dedicated MindStudio webhook URL. This is a powerful option for connecting MindStudio with other tools, platforms, and automation systems — no frontend or user input required.

This method is ideal for:

* **Zapier, Make, or N8N Integrations**: Run Agents when events occur in other tools.
* **Internal Automations**: Trigger workflows from internal scripts, bots, or microservices.
* **Web App Hooks**: Fire off AI logic when users perform certain actions in your product.
* **Data Pipeline Steps**: Pass structured data into an AI Agent mid-process.

## How It Works

When an Agent is configured with the **Webhook** run mode, MindStudio generates a unique webhook URL. Any system that can send an HTTP `POST` request can trigger the Agent.

The **only launch variable** for this mode is `webhookParams`, which must be a JSON object. Your workflow can then reference `{{webhookParams.key}}` to access individual values inside that payload.

For example, if your POST payload includes `{ "email": "user@example.com" }`, you can access it in your workflow as `{{webhookParams.email}}`.

## Key Features

* **Single Endpoint Simplicity**: One URL, one variable — clean and predictable.
* **Structured JSON Input**: Pass any number of fields via `webhookParams`.
* **Realtime Execution**: Fast responses for on-demand actions.
* **Platform Compatible**: Works seamlessly with any system that can send a POST request.
* **Secure by Design**: Webhook URL is unlisted and unique per Agent.
* **Full Access to Blocks**: Use inputs anywhere in the workflow, just like other variable types.

## Setup Requirements

To configure an AI Agent to run via webhook:

* Open the **Start Block** in your workflow.
* Set the **Run Mode** to `Webhook`.
* Ensure your workflow uses `{{webhookParams}}` to reference incoming data.
* Assign outputs to named variables (e.g., `summary`, `classification`).
* Publish your Agent.
* Copy the provided **Webhook URL** from the Trigger section.

To trigger the Agent:

```http
POST https://v1.mindstudio-api.com/dev/your-webhook-id
Content-Type: application/json

{
    "customerName": "Jane Doe",
    "question": "What is your return policy?"
}
```

Example reference inside the workflow:

* `{{webhookParams.customerName}}` → “Jane Doe”
* `{{webhookParams.question}}` → “What is your return policy?”


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://university.mindstudio.ai/deployment-of-ai-agents/webhook-triggered.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.