It includes everything you need to go from early prototypes to production-ready applications. Mastra integrates with frontend and backend frameworks like React, Next.js, and Node, or you can deploy it anywhere as a standalone server. It's the easiest way to build, tune, and scale reliable AI products.

Installation

@mastra/core is an essential building block for a Mastra application. We recommend following the installation guide to get started with Mastra.

You can install the package like so:

npm install @mastra/core

Core Components

Mastra (/mastra): Central orchestration class that initializes and coordinates all Mastra components. Provides dependency injection for agents, workflows, tools, memory, storage, and other services through a unified configuration interface. Learn more about Mastra
Agents (/agent): Autonomous AI entities that understand instructions, use tools, and complete tasks. Encapsulate LLM interactions with conversation history, tool execution, memory integration, and behavioral guidelines. Learn more about Agents
Workflows (/workflows): Graph-based execution engine for chaining, branching, and parallelizing LLM calls. Orchestrates complex AI tasks with state management, error recovery, and conditional logic. Learn more about Workflows
Tools (/tools): Functions that agents can invoke to interact with external systems. Each tool has a schema and description enabling AI to understand and use them effectively. Supports custom tools, toolsets, and runtime context. Learn more about Tools
Memory (/memory): Thread-based conversation persistence with semantic recall and working memory capabilities. Stores conversation history, retrieves contextually relevant information, and maintains agent state across interactions. Learn more about Memory
MCP (/mcp): Model Context Protocol integration enabling external tool sources. Supports SSE, HTTP, and Hono-based MCP servers with automatic tool conversion and registration. Learn more about MCP
Observability: Type-safe observability system tracking AI operations through spans. Provides flexible tracing with event-driven exports, configurable sampling, and pluggable processors and exporters for real-time monitoring. Full observability features are available in the @mastra/observability package. Learn more about Observability
Storage (/storage): Pluggable storage layer with standardized interfaces for multiple backends. Supports PostgreSQL, LibSQL, MongoDB, and other databases for persisting agent data, memory, and workflow state. Learn more about Storage
Vector (/vector): Vector operations and embedding management for semantic search. Provides unified interface for vector stores with filtering capabilities and similarity search. Learn more about Vector
Server (/server): HTTP server implementation built on Hono with OpenAPI support. Provides custom API routes, middleware, authentication, and runtime context for deploying Mastra as a standalone service. Learn more about Server
Voice (/voice): Voice interaction capabilities with text-to-speech and speech-to-text integration. Supports multiple voice providers and real-time voice communication for agents. Learn more about Voice
Browser (/browser): Base classes and utilities for browser automation. Provides the MastraBrowser abstract class, thread management, and screencast streaming for building browser providers. Use with @mastra/agent-browser or @mastra/stagehand for complete browser automation. Learn more about Browser

License

This package uses a dual-license model:

Apache License 2.0: The vast majority of this codebase is open source under Apache-2.0.
Mastra Enterprise License: Code in any directory named ee/ (e.g., @mastra/core/auth/ee) is source-available under the Mastra Enterprise License. These features require a valid enterprise license for production use but can be freely used for development and testing.

See LICENSE.md for the full license mapping and ee/LICENSE for the enterprise license terms.