@mastra/agent-builder

This package is currently experimental and only meant to be used internally to Mastra at the moment, the APIs are subject to change in this period.

A specialized AI agent for building production-ready Mastra applications, agents, tools, and workflows from natural language requirements.

Installation

npm install @mastra/agent-builder

Overview

@mastra/agent-builder is a meta-agent that helps developers create Mastra applications by:

• Agent Generation: Create specialized AI agents from natural language descriptions
• Tool Creation: Generate custom tools with proper schemas and validation
• Workflow Building: Design and implement complex multi-step workflows
• Project Management: Handle dependencies, configuration, and project structure
• Code Validation: Ensure generated code follows best practices and passes linting

Key Features

• Mastra Expert Knowledge: Deep understanding of Mastra patterns and conventions
• Production-Ready Code: Generates complete, working implementations
• Project Context Aware: Understands existing codebase structure and integrates seamlessly
• Quality Assurance: Built-in validation and testing capabilities
• MCP Integration: Leverages Model Context Protocol for enhanced tooling

Quick Start

import { AgentBuilder } from '@mastra/agent-builder';
import { openai } from '@ai-sdk/openai';

const builder = new AgentBuilder({
  model: openai('gpt-4'),
  summaryModel: openai('gpt-4'),
  projectPath: '/path/to/your/project',
});

// Generate an agent from natural language
const result = await builder.generate({ ... })

Configuration

The AgentBuilder requires a configuration object with:

• model: The primary language model for code generation
• summaryModel: A model for summarizing tool calls and results
• projectPath: Path to your Mastra project
• instructions: Optional additional instructions
• tools: Optional additional tools to include

Advanced Usage

Custom Project Management

// Install packages
const result = await builder.generate('Install @mastra/workflows package with latest version');

// Validate generated code
const validation = await builder.generate('Validate the TypeScript types and linting for src/agents/my-agent.ts');

Server Management

// Start development server
const serverResult = await builder.generate('Start the development server on port 4200');

// Test API endpoints
const testResult = await builder.generate('Test the /health endpoint at http://localhost:4200');

Memory and Processing

The AgentBuilder includes specialized memory processors:

• ToolSummaryProcessor: Caches and summarizes tool call results
• WriteToDiskProcessor: Saves conversation history for debugging
• TokenLimiter: Manages context window size

Best Practices

1. Provide Clear Requirements: The more specific your requirements, the better the generated code
2. Use Project Context: Let the agent explore your existing codebase structure
3. Validate Output: Always run the validation tools after code generation
4. Iterative Development: Start with simple agents and add complexity incrementally