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Mastra vs LangGraph

MastraLangGraph

Bottom line: Mastra for typeScript and full-stack JavaScript teams; LangGraph for engineering teams building production agents.

MastraMastra

The TypeScript framework for building AI agents and workflows.

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LangGraphLangGraph

Graph-based orchestration for stateful, controllable LLM agents.

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Votes00
PricingFreemiumFreemium
CategoryAgent FrameworksAgent Frameworks
Tags
agentstypescriptopen-sourceworkflowrag
agentsorchestrationllm-frameworkopen-sourceworkflow
Best for
  • TypeScript and full-stack JavaScript teams
  • Startups shipping AI features fast
  • Developers wanting agents without Python
  • Engineering teams building production agents
  • Developers needing controllable, resumable workflows
  • Teams already invested in LangChain
Pros
  • TypeScript-native, rare among serious agent frameworks
  • Open source and free to self-host
  • Ergonomic agents, workflows, memory, and evals in one toolkit
  • Strong funding and momentum (22k+ GitHub stars)
  • Fits full-stack and front-end teams
  • Explicit, debuggable control over agent state and flow
  • MIT-licensed core, free to self-host
  • Model-agnostic, not tied to one LLM vendor
  • Strong support for cycles, checkpointing, and human-in-the-loop
  • Backed by the widely used LangChain ecosystem
Cons
  • Young project with a still-maturing ecosystem
  • APIs may change as it evolves toward stability
  • Fewer integrations than older Python frameworks
  • TypeScript-only, no Python option
  • Managed cloud pricing not fully transparent
  • Steeper learning curve than high-level agent builders
  • Requires comfort with graph and state concepts
  • Paid platform and observability are separate products
  • Documentation and APIs have evolved quickly
  • Can be overkill for simple single-shot LLM tasks

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