LangGraph vs Mastra: Agent Frameworks Comparison
Compare LangGraph and Mastra side by side. Both are tools in the Agent Frameworks category.
Quick Comparison
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | — | Open Source |
| Best For | — | TypeScript developers who want a modern framework for building production AI agents |
| Website | langchain.com | mastra.ai |
| Key Features | — |
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| Use Cases | — |
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When to Choose LangGraph vs Mastra
- TypeScript-native agent development
- Building AI workflows with tool use
- Agent state management
How to Choose a Agent Frameworks Tool
Key criteria to evaluate when comparing Agent Frameworks solutions:
About LangGraph
LangGraph is LangChain's graph-based orchestration framework for building stateful, multi-step AI agents. It models agent workflows as directed graphs with nodes and edges, enabling complex control flow patterns like branching, looping, and human-in-the-loop interactions. LangGraph supports persistent state, streaming, and deployment via LangGraph Cloud.
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.
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 →