8 Best Mastra Alternatives in 2026 (Open Source)
Mastra — From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.. Unlike LangChain (Python-first, complex abstraction) or CrewAI (Python multi-agent), Mastra is purpose-built for TypeScript with native Next.js/React integration, graph-based workflows with .then()/.branch()/.parallel() syntax, and built-in evals — making it the most natural choice for JS/TS production agent development.
These 8 open-source tools do the same job. They are ordered by how closely they match Mastra, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Mastra(original) | 28.5k | +972 | 2026-09-30 |
| voltagent | 10.7k | +587 | 2026-09-28 |
| AI SDK | 27.1k | +644 | 2026-09-30 |
| langgraphjs | 3.3k | +99 | 2026-09-29 |
| Agno | 42.4k | +551 | 2026-09-30 |
| Lemon Agent | 350 | +0 | 2023-09-25 |
| Pydantic AI | 20.3k | +711 | 2026-09-30 |
| Eino | 13.2k | +468 | 2026-09-29 |
| LangChain | 147.3k | +23,453 | 2026-09-30 |
1. voltagent
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
What sets it apart: Full-stack TypeScript agent platform with built-in workflow engine, voice support, and observability console — more opinionated than Vercel AI SDK, more TypeScript-native than LangChain
Best for: TypeScript developers building production agent systems with observability; Multi-agent systems with workflow orchestration and voice capabilities
2. AI SDK
The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents
What sets it apart: Best-in-class TypeScript AI SDK with native UI hooks and Vercel integration — the React/Next.js standard for AI apps, unlike LangChain's Python-first approach
Best for: Full-stack TypeScript AI applications with React/Next.js; Building chatbots and generative UI with streaming
3. langgraphjs
Framework to build resilient language agents as graphs.
What sets it apart: The JavaScript/TypeScript graph-based agent framework from LangChain with built-in persistence, streaming, and human-in-the-loop — vs simpler agent libs lacking state management and controllability
Best for: Building complex, stateful JS/TS agents with controllable workflows; Production agents needing persistence, streaming, and human-in-the-loop; Teams already in the LangChain ecosystem
4. Agno
Build, run, manage agentic software at scale.
What sets it apart: Production-first agent runtime with built-in session isolation, approval workflows, and scalable FastAPI serving — unlike LangChain which is framework-first
Best for: Production multi-agent systems with session isolation; Enterprise agentic applications needing approval workflows and audit trails
5. Lemon Agent
Plan-Validate-Solve (PVS) Agent for accurate, reliable and reproducable workflow automation
What sets it apart: vs single-tool agents: dual Planner/Solver architecture with 120+ pre-configured business tool integrations and human-in-the-loop approval — built-in analytics for workflow optimization
Best for: Multi-step workflow automation across business tools; Scenarios needing transparent decision-making with approval gates; Connecting disparate business platforms (CRM, PM, comms)
6. Pydantic AI
AI Agent Framework, the Pydantic way
What sets it apart: Unlike LangChain (heavy abstraction, runtime errors) or CrewAI (multi-agent focus), Pydantic AI is built by the Pydantic team to deliver FastAPI-level type safety with dependency injection, durable execution, and composable capabilities — catching errors at write-time rather than runtime.
Best for: Python developers who value type safety and want a FastAPI-like experience for building production AI agents; Teams already using Pydantic who want structured, validated LLM outputs with minimal boilerplate
7. Eino
The ultimate LLM/AI application development framework in Go.
What sets it apart: The most mature LLM application framework for Go — vs LangChain/LlamaIndex which are Python/JS only
Best for: Go-based AI agent and RAG application development; Teams already in the CloudWeGo/ByteDance ecosystem
8. LangChain
The agent engineering platform
What sets it apart: vs other frameworks: Largest ecosystem with 100+ integrations, dual Python/JS support, backed by LangGraph for agent orchestration and LangSmith for production observability - the most widely adopted LLM framework
Best for: Building complex LLM applications with many integrations; Teams needing model interoperability and quick provider switching; Production AI applications requiring observability via LangSmith