Keywords AI

AutoGen vs Mastra

Compare AutoGen and Mastra side by side. Both are tools in the Agent Frameworks category.

Quick Comparison

	AutoGen	Mastra
Category	Agent Frameworks	Agent Frameworks
Pricing	Open Source	Open Source
Best For	Researchers and developers building multi-agent systems with structured conversation patterns	TypeScript developers who want a modern framework for building production AI agents
Website	microsoft.github.io	mastra.ai
Key Features	Multi-agent conversation framework Flexible agent communication patterns Code execution sandbox Human-in-the-loop support Microsoft-backed development	TypeScript agent framework Built-in tool calling and workflows Sync engine for agent state Integration marketplace Production-ready agent primitives
Use Cases	Multi-agent debate and collaboration Code generation with execution verification Research tasks requiring multiple perspectives Group chat agent orchestration Complex problem decomposition	TypeScript-native agent development Building AI workflows with tool use Agent state management Production agent deployment Multi-step task automation

When to Choose AutoGen vs Mastra

Choose AutoGen if you need

Multi-agent debate and collaboration
Code generation with execution verification
Research tasks requiring multiple perspectives

Pricing: Open Source

Choose Mastra if you need

TypeScript-native agent development
Building AI workflows with tool use
Agent state management

Pricing: Open Source

How to Choose a Agent Frameworks Tool

Key criteria to evaluate when comparing Agent Frameworks solutions:

Programming languagePython, TypeScript, or both — must match your team skills and existing codebase.

Architecture patternSingle-agent, multi-agent, or graph-based orchestration depending on task complexity.

Tool ecosystemBuilt-in tools and ease of creating custom tools for your specific needs.

ObservabilityBuilt-in tracing, debugging, and monitoring for understanding agent behavior.

Production readinessError handling, retries, streaming, and deployment options for production use.

About AutoGen

AutoGen is Microsoft's open-source framework for building multi-agent AI systems. It enables the creation of conversational agents that can work together, use tools, and interact with humans to solve complex tasks. AutoGen supports customizable agent behaviors, flexible conversation patterns, and integrations with various LLMs. The framework is popular for building research assistants, coding agents, and automated analysis pipelines.

View AutoGen profile →Visit website

About Mastra

Mastra is a TypeScript-first agent framework for building production AI applications. It provides primitives for agents, workflows, RAG, integrations, and memory with a focus on developer experience and type safety. Mastra is designed for full-stack TypeScript developers who want to build AI features without leaving their existing tech stack.

View Mastra profile →Visit website

What is Agent Frameworks?

Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.

Browse all Agent Frameworks tools →

Frequently Asked Questions

What is an AI agent framework?▾

An agent framework provides the building blocks for creating AI agents that can autonomously plan, use tools, and complete multi-step tasks. Instead of building tool use, memory, and orchestration from scratch, you get pre-built components that handle the common patterns.

Do I need a framework or can I build agents with raw API calls?▾

For simple single-tool agents, raw API calls work fine. Frameworks become valuable when you need multi-step planning, tool orchestration, error recovery, memory, or multi-agent coordination. They save significant development time for complex agent architectures.

Which agent framework should I choose?▾

LangChain and LlamaIndex are the most mature with the largest ecosystems. CrewAI is best for multi-agent workflows. Vercel AI SDK is ideal for TypeScript/Next.js applications. Evaluate based on your language preference, use case complexity, and integration needs.