Keywords AI

Mastra vs Swarm

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

Quick Comparison

Mastra
Mastra
Swarm
Swarm
CategoryAgent FrameworksAgent Frameworks
PricingOpen Source
Best ForTypeScript developers who want a modern framework for building production AI agents
Websitemastra.aigithub.com
Key Features
  • TypeScript agent framework
  • Built-in tool calling and workflows
  • Sync engine for agent state
  • Integration marketplace
  • Production-ready agent primitives
Use Cases
  • TypeScript-native agent development
  • Building AI workflows with tool use
  • Agent state management
  • Production agent deployment
  • Multi-step task automation

When to Choose Mastra vs Swarm

Mastra
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 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.

About Swarm

Swarm is OpenAI's experimental multi-agent orchestration framework that introduced the "handoff" and "routine" patterns for agent coordination. While marked as educational, its lightweight design — agents as instructions + functions with explicit handoffs between them — has become the dominant architectural pattern adopted across the industry for building multi-agent systems.

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.

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