PluginStackWhat it does
A TypeScript framework for AI apps and agents. It includes model routing across 40+ providers, agents with tools, graph-based workflows with suspend/resume, memory and RAG, MCP server authoring, evals and observability, plus a local Studio UI. Apache-2.0, except code in ee/ folders, which uses an enterprise license.
Who it's for
JavaScript and TypeScript developers who want to add agents to a Next.js, React or Node app.
How to set it up
Create a project:
bashnpm create mastra@latestFollow the prompts to pick a project name and model provider, then add your API key to .env.
Start the dev server and open Mastra Studio at http://localhost:4111 to test agents and workflows.
bashnpm run dev
Check the official Mastra docs for the latest steps.
Example prompts
Create a Mastra agent with a tool that fetches weather for a city.Build a Mastra workflow that pauses for human approval before publishing a post.Expose my Mastra tools as an MCP server.Demo
Demo coming soon
A short walkthrough of Mastra in action.
More Agent Frameworks
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- CrewAI
CrewAI
A Python framework for multi-agent automation. Crews are teams of role-based agents that work together on a task; Flows are event-driven workflows with state and branching that can call crews. The CLI scaffolds projects, which are JSON-first by default. MIT licensed.
- LangChain
LangGraph
A low-level framework for building long-running, stateful agents as graphs. It provides durable execution (agents resume after failures), human-in-the-loop interrupts and short- and long-term memory. It works on its own or with LangChain and LangSmith. A JS version (LangGraph.js) is also available. MIT licensed.
- OpenAI
OpenAI Agents SDK
A lightweight Python framework for building agents and multi-agent workflows. It covers agents with tools and handoffs, guardrails, human-in-the-loop, sessions, tracing, sandbox agents and voice/realtime agents. It works with OpenAI's APIs and, per the README, 100+ other LLMs. A JS/TS version exists too. MIT licensed.
- Pydantic
Pydantic AI
A typed Python agent framework from the Pydantic team. You define agents with typed outputs and tools, and switching model providers is a one-string change. Companion packages add a harness for long-running agents (files, shell, sub-agents) and Pydantic Evals for testing. MIT licensed.