mastra-ai/mastra

What it solves

Mastra solves the complexity of building and scaling production-ready AI agents and applications using a modern TypeScript stack. It provides a unified framework that bridges the gap between early prototypes and deployed software by integrating model routing, state management, and observability tools into a single ecosystem.

How it works

Mastra provides a set of core primitives for AI development:

• Model Routing: A standard interface to connect with over 40 different LLM providers (such as OpenAI, Anthropic, and Gemini).
• Agents: Autonomous entities that use LLMs and tools to reason through open-ended tasks and iterate until a goal is reached.
• Workflows: A graph-based engine for orchestrating multi-step processes with explicit control flow using syntax like .then(), .branch(), and .parallel().
• Context & Memory: Tools for managing conversation history, retrieving data from external sources (RAG), and implementing "Observational Memory" for coherent agent behavior.
• Human-in-the-loop: A system to suspend and resume executions based on user input or approval, utilizing storage to maintain state.
• MCP Servers: Support for authoring Model Context Protocol servers to expose agents and tools to other systems.

Who it’s for

TypeScript developers building AI-powered applications, specifically those using React, Next.js, or Node.js, who need a way to orchestrate complex agentic workflows and maintain production-grade observability.

Highlights

• Unified Model Interface: Access to 40+ providers through one standard API.
• Graph-based Orchestration: Precise control over AI execution paths via a workflow engine.
• Stateful Execution: Ability to pause and resume agents indefinitely via human-in-the-loop capabilities.
• Production-Ready Tooling: Built-in evaluation and observability tools for continuous refinement.
• TypeScript Native: Deep integration with the modern JS/TS ecosystem including Vercel AI SDK UI and CopilotKit.