> ## Documentation Index
> Fetch the complete documentation index at: https://docs.karada.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Tutorial: Quickstart Guide

> Get started with Karada and deploy your first Auto-MCP server in under 5 minutes.

Welcome to Karada! This tutorial walks you through the core flow of the platform: creating a project and transforming a standard REST API into an AI-ready Model Context Protocol (MCP) server.

**What you'll learn**:

* How to create a project in your workspace
* How to configure an Auto-MCP integration
* How to generate and deploy your MCP server

## Prerequisites

Before you begin, ensure you have:

* [ ] Created an account on [Karada.ai](https://karada.ai).
* [ ] A valid OpenAPI or Swagger URL (e.g., `https://api.example.com/openapi.json`). If you don't have one, use a public API like the [Petstore API](https://petstore.swagger.io/v2/swagger.json).

***

## Step 1: Create a Workspace and Project

A project serves as the top-level container for all your deployments, integrations, and usage tracking.

1. Navigate to your **Dashboard**.
2. If you haven't already, create a new **Team Workspace**.
3. Click the **Create Project** button in the top right corner.
4. Select the **Auto-MCP** template from the list of available providers.
5. Provide your project with a descriptive name (e.g., `Petstore AI Agent`).

***

## Step 2: Configure Auto-MCP

Karada's Auto-MCP feature converts any API into an intelligent tool.

<Steps>
  <Step title="Select Specification Type">
    Choose between **OpenAPI** or **Swagger** depending on the format of your
    API specification. Karada supports both widely-used standards.
  </Step>

  <Step title="Provide the API URL or File">
    Paste the URL pointing to your `.json` or `.yaml` specification file.
    Alternatively, upload the file directly from your local machine.
  </Step>

  <Step title="Review the Detected Tools">
    Karada parses the specification immediately. Review the list of detected
    endpoints, required parameters, and descriptions. These act as the exact
    tools your AI assistant will use.
  </Step>
</Steps>

***

## Step 3: Generate and Deploy

Once you review and approve the detected tools:

1. Click the **Generate Server** button.
2. Wait a few seconds while Karada automatically generates the MCP server.
3. Choose your preferred hosting method:
   * **Download as ZIP**: Run the server locally on your machine.
   * **Deploy to Karada**: Host the server instantly on the Karada infrastructure.

### Running Locally (Downloaded ZIP)

If you download the server to run locally, follow these steps to start it:

```bash theme={null}
# Unzip the downloaded folder
unzip karada-mcp-server.zip
cd karada-mcp-server

# Install dependencies
npm install

# Start the generated MCP server
npm start
```

## Next Steps

Now that you have your MCP server running, connect it to AI clients like the **Claude Desktop App** or **Cursor IDE**.

👉 **[Learn how to configure AI Clients in our Auto-MCP Deep Dive](/features/auto-mcp)**