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

# Quickstart

> Start building AI workflows in under 5 minutes

Get up and running with your first **MCP server** in just a few steps. This guide walks you through **signing in, deploying an MCP server, testing it in the Playground**, and **viewing traces**.

### Step 1: Sign In or Create an Account

Go to [platform.contexaai.com](https://platform.contexaai.com) and sign in using your credentials.
Don’t have an account? Click Sign Up to register in seconds.

### Step 2: Deploy Your MCP Server

Choose one of the following ways to deploy:

**🔍 Option 1: Use a Curated Server**

Navigate to the MCP Directory.
Browse verified servers contributed by the verified developers and organizations.
Click Deploy on any server to set it up instantly.

**🔗 Option 2: Bring Your Own Server**

Go to Directory > Add Server > via GitHub. [Deploy via Github](https://platform.contexaai.com/mcp-directory/github)
Enter public GitHub repo URL containing your MCP code.
Configure deployment settings and click Deploy.

**📄 Option 3: Create from OpenAPI Spec**

Navigate to Directory > Add Server > via OpenAPI. [Deploy via OpenAPI](https://platform.contexaai.com/mcp-directory/open-api)
Upload your OpenAPI 3.0 spec file or paste the spec in the editor.
Name your server and click Deploy.

### **Step 3: Test in the Playground**

Once your MCP server is deployed:

1. Go to the **Playground** section.
2. Select your **MCP server** from the dropdown list.
3. Choose an **LLM model** (e.g., GPT-4, GPT-4o, GPT-4o-mini).
4. Send a request and see **live responses** from your MCP server.
5. Optionally, **compare outputs** across different models to evaluate performance.

### **Step 4: View Traces & Logs**

* Navigate to **Traces**.
* **Platform Logs:** See all tool calls with timestamps, inputs, outputs, and status.
* **Server Session Logs:** View grouped logs by session for detailed analysis.
* Use filters to drill down into specific tools or calls.

### ✅ You’re All Set!

You’ve now:

* ✅ Signed in
* ✅ Deployed your first MCP server
* ✅ Tested it with real models
* ✅ Viewed logs and metrics

Start building **intelligent, composable tools** with the power of **Model Context Protocols and LLMs**.