Mastra
TypeScript · NOASSERTION
Mastra is a TypeScript-first agent platform that combines workflows, memory, RAG, evaluation, and deployment for scalable full-stack AI agent applications.
typescriptworkflowragfullstack
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Overview
Mastra vs LangGraph: TypeScript and Python Agent Orchestration Framework Comparison
Compare Mastra (TypeScript-first) and LangGraph (Python-first) across workflow, tool calling, state management, and observability.
Projects Compared
LangGraph
Python · MIT
LangGraph is a framework for building controllable, debuggable, long-running stateful agents, expressing agent state and control flow as a graph.
agent-frameworkstatefulgraphorchestrationpython
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Feature Comparison
| Best for | Mastra | LangGraph |
|---|---|---|
| Core positioning | TypeScript-first Agent framework with deep Next.js and React ecosystem integration, emphasizing API-first developer experience | Python-first state graph Agent framework from LangChain team, emphasizing graph orchestration and long-term memory |
| State management | Zod-based typed state management, state changes are serializable and replayable, aligned with React state management philosophy | Checkpointer-based persistent state, supports memory, file, Postgres, Redis and other backends |
| Tools and integration | Built-in Mastra Studio visual debugging, interoperable with Vercel AI SDK, supports MCP protocol | LangGraph Platform provides managed runtime and visual debugging, deep integration with LangChain ecosystem (200+ integrations) |
| Deployment and runtime | Supports Node.js process, Docker, Vercel Edge Functions, flexible deployment | Supports self-hosted (Docker), LangGraph Platform managed, LangGraph Studio three modes |
GitHub Stats
| Metric | Mastra | LangGraph |
|---|---|---|
| Stars | 26.4k | 37.7k |
| Forks | 2.5k | 6.3k |
| Language | TypeScript | Python |
| License | NOASSERTION | MIT |
| Last commit | July 21, 2026 | July 20, 2026 |
Which one should you choose?
Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.