vishesh-experiments/.experiments/getting-started-with-mastra.mdx

Production-ready integration patterns via MCP. Access battle-tested code from OSS contributions directly in your IDE.

---
title: "Getting Started with Mastra"
description: "Complete guide to building AI agents with Mastra framework, from setup to production"
category: "getting-started"
tags: ["mastra", "ai-agents", "nextjs", "typescript"]
date: "2024-10-03"
ossProject: "Mastra"
prLink: "https://github.com/mastra-ai/mastra"
---

# Getting Started with Mastra

Mastra is a powerful framework for building AI agents. In this experiment, I explored its core features and capabilities.

## Overview

This experiment covers:
- Setting up Mastra in a Next.js application
- Creating custom agents
- Integrating with external APIs
- Best practices for production deployments

<Callout type="info" title="Prerequisites">
You should have basic knowledge of TypeScript and Next.js before diving into this experiment.
</Callout>

## Installation

First, install the required dependencies:

```bash
pnpm add @mastra/core
```

## Creating Your First Agent

Here's a simple example of creating an agent:

```typescript
import { Agent } from '@mastra/core';

const myAgent = new Agent({
  name: 'assistant',
  instructions: 'You are a helpful assistant.',
  model: {
    provider: 'openai',
    name: 'gpt-4',
  },
});
```

## Key Learnings

Through this experiment, I learned:

1. **Architecture Design**: Mastra provides a clean separation between agent logic and application code
2. **Flexibility**: Easy to integrate with various LLM providers
3. **Production Ready**: Built-in features for logging, error handling, and monitoring

<Callout type="success">
Mastra simplified my agent development workflow significantly, reducing boilerplate code by ~60%.
</Callout>

## Next Steps

- Explore advanced agent patterns
- Implement custom tools
- Set up production monitoring

---

*This is a placeholder experiment. Replace with your actual technical content.*