An "AI agent framework" is just a toolkit for building software that can plan a multi-step task, call tools, and act mostly on its own — instead of a chatbot that only answers one question at a time. As teams move from single prompts to actual autonomous workflows, two names come up constantly in 2026: CrewAI and Mastra. Both let you assemble a team of AI agents that split up a task, but they're built for different programming ecosystems and different priorities. Here's how they actually compare.
The core difference in one line
CrewAI is a Python framework built for speed: role-based "Crews" of agents plus event-driven "Flows" for more deterministic control, with the fastest path from idea to a working multi-agent prototype. Mastra is a TypeScript framework built for completeness: typed tools, graph orchestration, and memory, RAG, evals and MCP support all bundled in from day one, behind a single interface to 90+ model providers.
Side by side
| CrewAI | Mastra | |
|---|---|---|
| Language | Python | TypeScript |
| Core license | MIT, free | Apache 2.0, free (some enterprise features dual-licensed) |
| Built-in memory/RAG/evals | Add-ons via Flows and integrations | Built in from the start |
| Community | 55k+ GitHub stars | Smaller, newer, growing fast |
| Paid tier | AMP Suite, priced on request | Cloud Teams tier, paid |
| Best for | Fast Python prototyping | Production TypeScript/Node apps |
CrewAI: the fastest way to prototype a multi-agent team
CrewAI's whole pitch is speed: you define agent roles, give them a goal, and it handles the coordination — which is why it has the biggest community of any agent framework here, at 55,000+ GitHub stars. Flows add a more deterministic, event-driven layer on top of Crews when you need less improvisation and more predictable control flow. The framework itself is MIT-licensed and free; there's a free control-plane tier, and an enterprise AMP Suite priced on request for teams that want more governance.
Where it falls short: the high-level abstractions that make it fast to prototype also hide a lot of what the agents are actually doing under the hood, which makes debugging harder once things get complex — and the dependency footprint is heavier than a minimal setup.
Mastra: the most complete TypeScript agent framework
Mastra's pitch is completeness rather than raw speed: memory, retrieval-augmented generation (RAG), evals and Model Context Protocol (MCP) support are all built into the core, rather than things you bolt on later — plus one interface to 90+ model providers, so switching models doesn't mean rewriting your integration. The core is Apache 2.0 and free; there's a free Starter tier on Mastra Cloud, with a paid Teams tier for larger deployments (some enterprise features carry a separate production license, worth checking before you ship).
Where it falls short: as a newer, faster-moving project, the API has seen more churn between releases than a mature framework, and the dual-licensing on certain enterprise features is something to verify before a production launch.
Which should you pick?
Pick CrewAI if your team is Python-first, you want to get a working multi-agent prototype running today, and you're comfortable adding memory, evals or guardrails yourself as the project matures.
Pick Mastra if you're building in TypeScript or Node.js and want memory, RAG, evals and multi-provider model support working together out of the box, without assembling them from separate libraries.
Both frameworks list each other as direct alternatives, along with LangGraph and LlamaIndex — a sign of how much this space is still converging on patterns rather than a single standard. If you're not sure yet, the honest test is to build the smallest real version of your workflow in both and see which one gets out of your way faster. You can dig into the full profiles of CrewAI and Mastra for pricing details, more alternatives, and additional pros and cons.